https://riseof.ai/talks/a-european-perspective-on-a-regulatory-framework-for-ai-big-data-and-m/https://i.ytimg.com/vi/gKs-tJnNUeg/hqdefault.jpgA European Perspective on a Regulatory Framework for AI, Big Data and ML – Damian Boeselager (Rise of AI Summit 2020)At Rise of AI 2020 in Berlin, Damian Boeselager, a Member of the European Parliament and co-founder of the pan-European party Volt, argues that AI and data regulation should be set at the European level rather than fragmented nationally. He describes how the European Commission paired Margrethe Vestager's AI strategy, which classifies applications as high or low risk, with a data strategy from Thierry Breton aimed at enabling data sharing across industries. Boeselager lays out three theses: prioritize EU-wide rules over national fragmentation to protect the digital single market; separate digital sovereignty from competitiveness by strengthening competition law and interoperability rules rather than building state-backed European cloud competitors such as GAIA-X; and make regulation concrete and tangible, citing GDPR as a global standard that nonetheless burdened small organizations like his own. He points to Sweden's regional-cluster approach as a model for helping SMEs move from analog operations to using AI. In the Q&A he addresses GAIA-X, data-sharing mandates for big tech, and how to make industrial data usable without destroying startups' competitive advantage.https://www.youtube.com/embed/gKs-tJnNUeg18002020-11-23T00:00:00+00:00yes https://riseof.ai/talks/a-paper-tiger-aiming-for-the-moon-can-germany-make-ai-aljoscha-burchar/https://i.ytimg.com/vi/STRzyx06lH4/hqdefault.jpgA Paper Tiger Aiming for the Moon: Can Germany Make AI? – Aljoscha Burchardt, Mario Brandenburg (Rise of AI Summit 2020)At Rise of AI Summit 2020, DFKI deputy site director Aljoscha Burchardt and Bundestag member Mario Brandenburg (FDP) discuss two years spent together on the German parliament's Enquete Commission on Artificial Intelligence, and whether Germany can move past being a policy 'paper tiger.' Burchardt explains he joined the commission almost by accident, sent to a meeting with FDP leader Christian Lindner in place of DFKI's then head, and was later nominated by Brandenburg to the 100-member body split between politicians and outside experts. They describe concrete recommendations, including requiring large platforms to give researchers API access to study hate speech and social bots, and an unresolved, evenly split vote on whether AI technology is neutral. They discuss Germany's shift from sixteen regional AI clusters to five centers of excellence, a pay rule that discouraged DFKI from hiring international researchers, government-backed startup funding, and debates over classroom eye-tracking and platform data access. They close by trading wishes: Burchardt wants the state to become an AI early adopter, Brandenburg wants better long-term monitoring of the commission's recommendations and more direct science communication to the public.https://www.youtube.com/embed/STRzyx06lH423402020-11-23T00:00:00+00:00yes https://riseof.ai/talks/actual-vc-perspectives-on-ai-christian-nagel/https://i.ytimg.com/vi/8YKK4hezb0s/hqdefault.jpgActual VC perspectives on AI – Christian Nagel (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Christian Nagel, Partner at Earlybird Venture Capital, argues that Europe is more competitive in AI than commonly assumed and lays out how his firm evaluates AI startups. He notes Europe produced 17 unicorns against China's 20 in the prior year, with UiPath, a Romanian company, becoming Europe's most valuable AI company and the fastest-growing enterprise software company ever, reaching an almost 400 million dollar run rate and a 7 billion dollar valuation. He says roughly a third of Earlybird's portfolio and deal flow involves AI, though the firm avoids investing on AI hype alone. He distinguishes descriptive, predictive and increasingly autonomous or self-driving AI applications, and separates vertical approaches (deep in one industry, citing a payment-fraud detection company) from horizontal ones (UiPath's robotic process automation across industries). His central investment criterion is data-driven lock-in: whether a company's algorithm improves enough with more data and customers to create a forward-looking advantage competitors cannot catch. He closes on the resulting chicken-and-egg problem of needing customers to get data and data to get customers.https://www.youtube.com/embed/8YKK4hezb0s12602019-07-18T00:00:00+00:00yes https://riseof.ai/talks/agentic-ai-and-data-spaces-europe-s-operating-system-for-the-future-ec/https://i.ytimg.com/vi/LeAuUWcxQRY/hqdefault.jpgAgentic AI and Data Spaces: Europe’s Operating System for the Future Economy – Chris Boos (Rise of AI Conference 2026)At Rise of AI 2026 in Berlin, Chris Boos argues that Europe has the lifestyle, security and knowledge base to lead in AI but is failing to act, citing 27 unimplemented national AI strategies against clear US and Chinese approaches. He frames sovereignty as the ability to control dependencies, not autarky, since no economy can be fully self-sufficient, and argues Europe's real asset is knowledge, not energy or raw materials, which it has never turned into a shared platform. Boos walks through a data-information-knowledge-intelligence-wisdom hierarchy, arguing that data is never "true" but a propagation of interactions through a system, and that Europe over-focuses on data transport instead of adding semantic, causal meaning that lets machines and humans work together on complex networks. He describes large language models as an interface technology comparable to the web browser, letting non-experts operate complex systems, and argues agentic AI's main risk to work is not job loss but the loss of "training ground" through which experts traditionally build skill. He closes urging curiosity over security, community over self, facts over feelings, and treating people with intrinsic respect regardless of role.https://www.youtube.com/embed/LeAuUWcxQRY17402026-07-15T00:00:00+00:00yes https://riseof.ai/talks/agentic-ai-in-classified-domains-dennis-geisse/https://i.ytimg.com/vi/N3KAGoRIAns/hqdefault.jpgAgentic AI in Classified Domains – Dennis Geisse, Robert Friedrich (Rise of AI Conference 2026)At Rise of AI 2026 in Berlin, a panel with Dennis Geisse (HPE), Robert Friedrich (Nvidia) and Anna from deepset presents a jointly built solution for deploying agentic AI in classified and highly sensitive environments, developed together with secunet. Robert Friedrich traces the idea back to a US government white paper on agentic AI and momentum from Davos, and describes projects like an Agentic AI Hub and an initiative called Spark. Anna explains that deepset's public-sector and defense customers kept asking whether AI tools were BSI certified, where models were hosted and whether deployments could run fully on premises, which pushed the partners to build a packaged, self-hosted "private cloud for AI" combining secunet's certified security layer, HPE's data and compute infrastructure, Nvidia's GPUs and open-source Nemotron models, and deepset's Haystack orchestration layer. Anna demonstrates a multi-agent situational-awareness system called Aida, built from observation, assessment and interaction agents, that keeps a human in the loop for critical decisions. Dennis Geisse walks through the resulting platform interface. In Q&A, the panel discusses incident response for on-premises agent deployments and where automation should stop in defense contexts.https://www.youtube.com/embed/N3KAGoRIAns18002026-07-15T00:00:00+00:00yes https://riseof.ai/talks/ai-a-double-edged-promise-christian-t-scha-fer/https://i.ytimg.com/vi/XciKOEb2zEw/hqdefault.jpgAI – a double-edged promise – Christian T. Schäfer (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, Christian T. Schäfer, head of the Deloitte Analytics Institute, argues that AI is a double-edged promise: enormous business value alongside real risks around trust, liability, security and control. He frames AI as a wide array of technologies rather than one thing, distinguishes today's narrow AI from a hoped-for general AI, and traces a hardware-driven history from the web and cloud to falling storage costs and specialized chips like Google's TPUs. He lays out risks including autonomous weapons, an AI arms race, loss of control over robust self-preserving systems, and data privacy, alongside potential upside such as recursive self-improvement, help with war, disease and poverty, and automation combined with universal basic income. He explains deep learning as a subset of machine learning that handles messy real-world data well, cites Deloitte's client demand data across five use-case areas, and closes by urging that a human-centered front end and process design, not just algorithms, determine business outcomes.https://www.youtube.com/embed/XciKOEb2zEw9602018-06-10T00:00:00+00:00yes https://riseof.ai/talks/ai-data-match-made-in-heaven-christian-winterfeldt/https://i.ytimg.com/vi/1OuvTqmKwOk/hqdefault.jpgAI & Data – Match Made in Heaven – Christian Winterfeldt (Rise of AI Conference 2024)At Rise of AI 2024 in Berlin, Christian Winterfeldt, Senior Director of Data Center Sales Germany at Dell Technologies, argues that AI models should be brought to a company's data rather than the reverse, for latency, cost and sovereignty reasons. He says roughly one-third of worldwide AI compute already runs on Dell infrastructure, and contrasts triple-digit-billion infrastructure investments in North America and Asia-Pacific with more cautious, but leading-edge, German experimentation. He cites data leaks at Amazon and Samsung, hallucinated legal citations, and a biased AI photo-editing example as cautionary cases, and reports survey findings that most companies interviewed prefer running AI on-premises. He walks through Dell's approach: embedding AI in products, running AI on Dell's own portfolio, using AI internally, and partnering across an ecosystem including Nvidia. He describes moving from generic downloaded models toward retrieval-augmented, fine-tuned models built on a governed 'AI-ready data platform' and data lakehouse, and outlines Dell's staged consulting approach: focus area, use case selection, and right-sized infrastructure.https://www.youtube.com/embed/1OuvTqmKwOk12602024-05-21T00:00:00+00:00yes https://riseof.ai/talks/ai-humans-new-form-of-super-humans-kevin-warwick/https://i.ytimg.com/vi/EGPMqj_-4X8/hqdefault.jpgAI + humans = new form of super humans? – Kevin Warwick (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, Kevin Warwick, Professor of Cybernetics, argues that rather than AI acting against humans, linking human nervous systems directly to AI and technology can upgrade human capability, and presents a series of experiments he has personally run rather than theoretical proposals. He describes an early RFID implant in his own arm that let a building recognize him, cultures of rat and later human brain cells (up to about 60 million cells) that learn through Hebbian learning to control a small robot's movement, and deep brain stimulation work with neurosurgeon Tipu Aziz for Parkinson's disease, where an AI system classifies disease subtype and predicts tremor onset 10 to 20 seconds in advance from electrode signals sent to a system located 30-35 miles away. He then describes his own BrainGate implant, used to control a robot hand over the internet between New York and England, to sense distance through ultrasonic pulses while blindfolded, and to exchange a basic telegraphic signal directly between his and his wife's nervous systems, which he presents as an early step toward brain-to-brain and brain-to-machine communication.https://www.youtube.com/embed/EGPMqj_-4X815002018-06-10T00:00:00+00:00yes https://riseof.ai/talks/ai-and-quantum-computing-transforming-the-digital-landscape-sabina-jes/https://i.ytimg.com/vi/eP5nMC55Gcc/hqdefault.jpgAI and Quantum Computing Transforming the Digital Landscape – Sabina Jeschke (Rise of AI Conference 2023)At Rise of AI 2023 in Berlin, Sabina Jeschke, CEO of KI Park e.V. and CIO at Quantagonia, argues that quantum computing is the next technology, alongside 5G/6G connectivity, that will push artificial intelligence beyond today's algorithm-driven phase of deep learning and reinforcement learning. She debunks four common assumptions: that quantum computing is too far away (deep-temperature systems reach industrial scale by 2025, room-temperature systems by 2028), that it only applies to niche research, that no usable quantum computers exist yet, and that it is too expensive. She frames quantum computing as unlocking problems that classical computing cannot execute in time, structured around optimization, simulation and AI, and illustrates this with cases from liquid gas routing, aircraft maintenance logistics, finance, fraud detection and reinforcement learning for autonomous driving. She closes by linking quantum computing to sustainability through orbital solar power, quantum-optimized flight paths and lower long-term energy use than commonly assumed.https://www.youtube.com/embed/eP5nMC55Gcc19202023-05-14T00:00:00+00:00yes https://riseof.ai/talks/ai-and-the-future-of-warfare-ulrike-franke/https://i.ytimg.com/vi/xsye4-YQQyY/hqdefault.jpgAI and the Future of Warfare – Ulrike Franke (Rise of AI Virtual Chat 2020)In this Rise of AI Virtual Chat from August 2020, Fabian Westerheide interviews Dr. Ulrike Franke, policy fellow at the European Council on Foreign Relations, about AI and the future of warfare. Franke argues AI will not end war, drawing a parallel to the earlier hope that nuclear weapons would make conflict too terrible to happen, and insists new military technology has historically added capability rather than removing human cost. She explains that military AI spans a full range from simple automation to fully autonomous 'terminator' weapons, citing Google's Project Maven surveillance work for the Pentagon as a real but non-lethal example. She sets out five reasons militaries want AI-enabled systems: speed, stealth, cost and efficiency, fewer personnel needed, and entirely new capabilities such as drone swarming. The conversation covers slow military procurement, the shift of cutting-edge research from state-funded to civilian labs, the U.S. Marines dropping Chinese-made DJI drones over data-security concerns, debates on keeping humans in the kill chain, the unlikelihood of a global autonomous-weapons ban, and Europe's under-studied but real military AI activity and defense posture.https://www.youtube.com/embed/xsye4-YQQyY37202020-08-06T00:00:00+00:00yes https://riseof.ai/talks/ai-as-platform-ramin-assadollahi/https://i.ytimg.com/vi/Wr5Zjhi6EHk/hqdefault.jpgAI as platform – Ramin Assadollahi (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, Ramin Assadollahi, CEO of ExB, argues that AI should be built as a cross-industry platform rather than as single-purpose solutions. He recounts inventing the next-word prediction technology used in mobile keyboards, sold to Nokia and scaled to 72 languages on Symbian Series 60 devices, and describes how ExB now applies one platform across health, mobility and finance, processing text, images and structured data in the cloud, on phones and offline in cars. He sets out three goals: reducing the cost per AI experiment, building data loops so systems keep learning from the errors a workflow corrects, and combining data modalities to gain performance and quality. Examples include extracting disease-related claims from medical publications, building a knowledge graph of automotive parts from technical documents, and a project for a German car manufacturer that predicts user behavior and answers questions about a car by mapping its internal states to language, which he calls referential semantics. He also describes closing data loops between vehicle design and after-sales repair reports, and warns that entity recognizers trained on one domain fail on another.https://www.youtube.com/embed/Wr5Zjhi6EHk12002018-06-10T00:00:00+00:00yes https://riseof.ai/talks/ai-business-models-rasmus-rothe/https://i.ytimg.com/vi/_zh7f03zAtI/hqdefault.jpgAI Business Models – Rasmus Rothe, Adrian Locher (Rise of AI Virtual Chat 2020)In this Rise of AI Virtual Chat from 2020, host Fabian Westerheide interviews Rasmus Rothe and Adrian Locher, founders of the AI venture studio Merantix AG, about how to make money with AI. They explain Merantix's model of building and funding AI companies over a ten-plus year horizon, validating business model, technology and team before startups raise external Series A funding, and describe screening entrepreneurs through interviews and a two-day on-site challenge, talking to about 300 candidates to find a handful of entrepreneurs-in-residence. They discuss where current AI opportunities lie, from mature computer vision to an emerging wave in natural language processing and longer-term bets like biology and neuroscience, and how AI creates business value through both automation and improved accuracy over human decision-making. They describe Merantix's own portfolio, including a services arm, a certified medical imaging product for breast cancer screening, and a sensor-data platform for automated driving. The conversation closes with a debate on what Europe needs to compete with the US and China, and audience questions on AI and climate change, B2C strategy, cloud choice and how they define AI.https://www.youtube.com/embed/_zh7f03zAtI39602020-06-15T00:00:00+00:00yes https://riseof.ai/talks/ai-business-models-trends-rasmus-rothe/https://i.ytimg.com/vi/NgLMZ5j3UOI/hqdefault.jpgAI Business Models & Trends – Rasmus Rothe (Rise of AI Summit 2020)At the Rise of AI Summit 2020, Dr. Rasmus Rothe, CTO and co-founder of the Berlin venture studio Merantix, presents trends in AI industries, technology and business models. He describes Merantix's model of working with individual founders for six to twelve months, investing up to three million euros per company, and building AI-first ventures such as Vara in breast cancer imaging, a data-management company he refers to as Sea Search, Merantix Labs for custom client solutions, and the newer Causa and Cambrian, with plans for eight more companies over the next four years, for ten new ventures in total. He argues the next frontier lies in 'dual PhD problem' areas that combine deep AI expertise with equally deep domain expertise, such as healthcare or synthetic biology, rather than the execution-heavy consumer startups of the past decade. On technology, he highlights GPT-3's shift from task-specific fine-tuning to a single 175-billion-parameter model trained on broad internet text, demonstrated through email drafting, balance-sheet filling and code generation. On business models, he outlines a spectrum from fully standardized products to full consulting, arguing the most promising middle ground is self-service, customizable AI products.https://www.youtube.com/embed/NgLMZ5j3UOI17402020-11-30T00:00:00+00:00yes https://riseof.ai/talks/ai-computing-power-at-the-edge-industry-use-cases-evgeniy-vlasov/https://i.ytimg.com/vi/PgRXzUFDWyg/hqdefault.jpgAI Computing Power at the Edge: Industry Use Cases – Evgeniy Vlasov (Rise of AI Summit 2020)At Rise of AI Summit 2020 in Berlin, Evgeniy Vlasov, senior alliance and business development manager at Huawei Technologies, explains why AI processing is moving from data centers to the edge, close to where data is generated. He argues that classical CPUs are not built for AI workloads and that over 90 percent of edge AI use cases today are inference rather than training, so edge devices need dedicated chipsets and must balance computing power against energy consumption, especially for battery-powered robots and drones. He presents Huawei's Atlas edge AI stack, including the Atlas 200 module, Atlas 500 edge station and Atlas 300 inference card, built on Huawei's own chipsets and the open-source MindSpore framework, which also supports third-party hardware and frameworks such as TensorFlow and PyTorch. He then walks through concrete deployments: autonomous delivery vehicles from partner Neolix, computer-vision quality control in manufacturing, and fleet management for automated guided vehicles with partner Gestalt Robotics, arguing edge devices work alongside the cloud rather than replacing it.https://www.youtube.com/embed/PgRXzUFDWyg15602020-11-30T00:00:00+00:00yes https://riseof.ai/talks/ai-enabling-automated-maintenance-hayri-g-cke/https://i.ytimg.com/vi/qk_dsyojgzw/hqdefault.jpgAI Enabling Automated Maintenance – Hayri Göcke (Rise of AI Conference 2023)At Rise of AI 2023, Hayri Goecke, Head of Growth at Gestalt Robotics, presents how his company applies computer vision and machine learning to automate maintenance for safety-critical mobility operations, focused on the E-Check project with Deutsche Bahn. Founded in 2016 and grown to 60 people without venture capital, Gestalt Robotics builds software modules that run on hardware from vendor-agnostic partners across computer vision, mobile robotics, arm robotics and worker-assistance systems. Goecke explains that Deutsche Bahn's growing train fleet is roughly doubling maintenance needs while a new maintenance site costs about 400 million euros to build, so the company is instead digitizing five existing sites with a 32-camera gate that scans each ICE train's underside at about 5 km/h, producing roughly 6,500 images and 30 gigabytes of data per wagon. He describes the technical challenge of producing precise, reproducible images across different trains, the on-site edge computing and cloud processing behind the system, and the close but clearly defined supplier relationship with Deutsche Bahn, including regular scrum-based feedback.https://www.youtube.com/embed/qk_dsyojgzw14402023-05-14T00:00:00+00:00yes https://riseof.ai/talks/ai-factories-at-scale-thomas-schmidt/https://i.ytimg.com/vi/zgO0tLpuHD4/hqdefault.jpgAI Factories at Scale – Thomas Schmidt (Rise of AI Conference 2024)At Rise of AI 2024 on the Applied AI Stage, Thomas Schmidt, founder of AMBER AI & Data Science Solutions GmbH, explains what it takes to build and operate large-scale AI infrastructure, or 'AI factories', for enterprise customers. AMBER grew out of Fluid, a company his co-founder, a professor at the Technical University of Munich, started in 2006 as one of Nvidia's earliest partners; it was acquired by US simulation company Altair in 2016, and Schmidt's team spun out as AMBER in 2022 to focus on AI infrastructure. He argues that GPU-based computing saves rather than wastes power compared to legacy CPU servers, illustrating this with a comparison between a 2012 supercomputer and a 2023 Nvidia DGX H100 system delivering more performance at a fraction of the cost and power draw. He outlines the three components of an AI factory, compute, storage and networking, warns that compute needs are growing 256 times every two years since transformers, and describes the shift toward liquid-cooled data centers as GPU racks reach a thousand watts and several tons per system. He closes by previewing an immersion-cooled AI cloud AMBER is building in Germany with partners Itera and Sustainable Metal Cloud.https://www.youtube.com/embed/zgO0tLpuHD416202024-05-21T00:00:00+00:00yes https://riseof.ai/talks/ai-for-a-better-world-generative-ai-to-drive-impact-and-esg-ronny-fehl/https://i.ytimg.com/vi/Qq_UXytyZRY/hqdefault.jpgAI for a Better World: Generative AI to Drive Impact and ESG – Ronny Fehling (Rise of AI Conference 2023)At Rise of AI 2023 in Berlin, Ronny Fehling, Partner and Vice President Artificial Intelligence at BCG X, argues that generative AI is a step change that complements rather than replaces traditional AI, and lays out how he guides C-suite executives through adopting it. He walks through a ladder of implementation options, from out-of-the-box chatbots and intelligent document processing to fine-tuning and building custom foundation models, warning that fine-tuning is expensive and prone to overfitting. He recommends mapping use cases by business impact and feasibility rather than starting with the easiest option, so unstructured company data, which he says makes up to 80 percent of enterprise data, can be turned into competitive advantage. The second half describes a project BCG X built for its own diversity, equity and inclusion data, using generative AI to quantify patterns in feedback text, such as women receiving more unconditional praise than men, and to measure the effect of recruiting initiatives. He closes by warning that competitors who move first on generative AI will gain efficiency advantages that are hard to reverse.https://www.youtube.com/embed/Qq_UXytyZRY16802023-05-14T00:00:00+00:00yes https://riseof.ai/talks/ai-for-customer-experience-michael-brehm/https://i.ytimg.com/vi/zeLfm5QTea4/hqdefault.jpgAI for Customer Experience – Michael Brehm (Rise of AI Virtual Chat 2021)In a 2021 Rise of AI Virtual Chat held with AWS, Fabian Westerheide interviews Michael Brehm, CEO of i2x, about AI-driven customer experience and the wider European deep tech ecosystem. Brehm describes i2x's real-time voice analytics product, built on the company's own speech-to-text engine, which gives call center agents live coaching during customer calls in under half a second, and argues full automation of human-to-human phone conversations remains more than a decade away. He argues Europe and Germany produce strong research and patents but fail to convert them into scaled applications and companies, contrasting a roughly 150 billion euro valuation for the whole European deep tech startup sector with TikTok's similar valuation as a single AI-driven product. He covers i2x's consent-based approach to handling call data, including anonymization and access controls, and closes with broader reflections on AI's effect on productivity, employment and wealth concentration, and on the fragmentation of the internet into US, Chinese, Russian and other regulatory blocs, plus practical details on i2x's use of AWS cloud infrastructure.https://www.youtube.com/embed/zeLfm5QTea436002021-02-26T00:00:00+00:00yes https://riseof.ai/talks/ai-for-security-and-risks-aleksandar-stojanovic/https://i.ytimg.com/vi/1B2NP8nDIkQ/hqdefault.jpgAI for Security and Risks – Aleksandar Stojanovic (Rise of AI Virtual Chat 2020)In this Rise of AI Virtual Chat recorded live in April 2020, Fabian Westerheide interviews Aleksandar Stojanovic, chairman and co-founder of AVA, an AI company he started in 2014 after earlier careers in music production and management consulting. Stojanovic describes AVA as a 'fusion platform' that pulls in social media, local and international news, professional intelligence feeds and sensor data, standardizes it, and uses machine learning plus human labeling to give organizations a contextualized, real-time picture of security risk, rather than predicting individual crimes. He walks through clients including DHL, the London Metropolitan Police and Deutsche Bahn, a live map demo of historical incidents in New York, and how AVA combines organizational, epidemiological and socio-political data to help multinational companies assess pandemic risk, citing the Canadian company BlueDot's early COVID-19 detection through the ProMED physician network. He also addresses privacy, arguing AVA, built after GDPR, deliberately avoids personal profiling and instead aims to democratize access to security intelligence historically available only to the wealthy.https://www.youtube.com/embed/1B2NP8nDIkQ38402020-05-04T00:00:00+00:00yes https://riseof.ai/talks/ai-for-society-shaping-a-positive-future-elisabeth-l-orange/https://i.ytimg.com/vi/Vj7Xbad-AxQ/hqdefault.jpgAI for Society: Shaping a Positive Future – Elisabeth L’Orange, Kenza Ait Si Abbou, Annika von Mutius, Nikolaus Roettger (Rise of AI Conference 2025)At Rise of AI 2025 in Berlin, a panel with Elisabeth L'Orange (Deloitte), Kenza Ait Si Abbou (FIEGE), Dr. Annika von Mutius (Empion, KI Bundesverband) and moderator Nikolaus Roettger (FutureStory) discusses how AI can benefit society beyond the circle of people already working with it. The panelists trace their own paths into AI, from academic mathematics and a university neural-network class to consulting and company-building, then debate whether the wider public needs to be excited about AI or simply needs enough trust and literacy to use it well. Von Mutius argues most business users do not need deep technical competence, only clear economic value, citing Germany's roughly six to seven percent AI adoption rate against far higher figures in the US and China. Ait Si Abbou stresses that legacy IT systems, not lack of enthusiasm, are the real barrier for many German companies, and that involving end users in building tools drives adoption. The panel also discusses Klarna's reversal on replacing call-center agents with AI, the risk of AI-amplified disinformation, and closes with differing personal optimism scores about AI's impact on society.https://www.youtube.com/embed/Vj7Xbad-AxQ27602025-05-21T00:00:00+00:00yes https://riseof.ai/talks/ai-has-finally-arrived-fabian-westerheide/https://i.ytimg.com/vi/wdxmPASlAuA/hqdefault.jpgAI Has Finally Arrived – Fabian Westerheide (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, in his opening keynote "AI has finally arrived," Fabian Westerheide, founder of Rise of AI and the venture capital firm Asgard, traces the conference's growth from a 2014 dinner discussion with 14 people to a sold-out event with 600 attendees, three stages and 55 speakers. He explains the day's structure: an AI Future stage on AGI, ethics and consequences, an Applied AI stage on adoption best practices, and a startups and investors stage. He presents new data from a landscape mapping project done with a partner he calls Wollenburger: of roughly 7,500 companies worldwide claiming to work on AI, about half were removed as not genuine, leaving 3,445 companies in the database, with around 40% based in the US, 11% in China and Israel combined, and only about 700 in Europe, where Germany holds roughly a 3% market share. He argues Europe risks becoming dependent on US or Chinese AI embedded in hardware, and calls for a shared European vision, a faster strategy than the EU's planned two-year process, more AGI-focused research, more funded AI startups and more capital. He announces that Asgard is opening its fund to semi-professional and professional investors from 1 July.https://www.youtube.com/embed/wdxmPASlAuA10802018-06-10T00:00:00+00:00yes https://riseof.ai/talks/ai-healthcare-a-cybernetic-perspective-martin-ciupa/https://i.ytimg.com/vi/BHNLezRvW54/hqdefault.jpgAI Healthcare – A Cybernetic Perspective – Martin Ciupa (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Martin Ciupa, chief artificial intelligence officer at MindMaze, argues that AI and virtual reality in neurological healthcare, especially stroke rehabilitation, should be understood through a cybernetics lens of feedback and control loops rather than as bottom-up AI alone. He frames the problem as a growing healthcare crisis: a shrinking number of healthcare professionals per capita, rising neurological damage from increased longevity, and expensive diagnostic and therapy technology, and cites a PwC estimate that AI will contribute 15.7 trillion pounds cumulatively by 2030. He describes MindMaze's MindMotion Pro and MindMotion Go products, which use motion sensing, gamification and AI-driven recommendation engines to deliver personalized, dosage-optimized therapy to stroke patients in the sub-acute and chronic recovery phases, including a 'whack-a-mole' style game that adapts to a patient's kinematic movement. He also describes using EMG and EEG sensors for affective computing, which he calls 'artificial empathic intelligence,' to detect patient fatigue or distraction during unsupervised home therapy. He closes by tracing cybernetics back to pacemakers and brain-machine interfaces such as the Walk Again Project, and frames MindMaze's approach as a continuous, data-driven feedback loop across diagnosis, therapy and prognosis.https://www.youtube.com/embed/BHNLezRvW5419802019-09-04T00:00:00+00:00yes https://riseof.ai/talks/ai-in-5-50-and-500-years-daniel-jeffries/https://i.ytimg.com/vi/01kPat84a8g/hqdefault.jpgAI in 5, 50 and 500 Years – Daniel Jeffries (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Daniel Jeffries lays out predictions for artificial intelligence across three horizons: five to fifteen years, fifty years and five hundred years. He argues that near-term change is slower than hype suggests, and that AI is a dual-use technology that reflects the values of its creators. In healthcare he expects faster triage and diagnosis, pointing to a 2017 Kaggle competition that produced lung cancer detection algorithms now used in hospitals. He describes a shift toward "Centaur" human-AI teams, a term drawn from Garry Kasparov's freestyle chess tournaments, and cites Stitch Fix as an example of AI-driven design paired with a human in the loop. He warns that China's lighter approach to data privacy, illustrated by an Alibaba-backed "city brain" system that a leaked, unsecured police database showed was tracking dissidents, could make China the world's AI training center while the EU and US debate ethics. Looking further out, he foresees the human connectome project enabling new chip designs, ubiquitous smart devices and self-driving trucks, and at five hundred years predicts humanity becomes "post-human" through deep integration with machines.https://www.youtube.com/embed/01kPat84a8g10802019-07-01T00:00:00+00:00yes https://riseof.ai/talks/ai-in-china-europe-and-usa-hans-uszkoreit/https://i.ytimg.com/vi/LxzjvLhKXMI/hqdefault.jpgAI in China, Europe and USA – Hans Uszkoreit (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Hans Uszkoreit compares the state of AI research and commercialization in China, the United States and Europe, and challenges Kai-Fu Lee's claim in AI Superpowers that Europe is not even competing for a bronze medal in the AI race. Uszkoreit argues Lee's framework focuses only on commercialization and product research, and that a fuller picture including basic research tells a different story: Europe still leads in publication volume and produces many of the pioneering researchers behind deep learning, even though the US dominates top-conference papers and best-paper awards and China leads in scale of funding and market size. He attributes US strength to decades of strategic DARPA funding that created a virtuous circle of research, commercialization and venture capital, and attributes China's fast growth to government dedication, market size, public awareness of AI figures and pragmatism about shipping minimum viable products. He closes by arguing Europe has real chances in enterprise AI, robotics, health and smart energy, and urges closer research cooperation between Europe and China rather than reliance on the US.https://www.youtube.com/embed/LxzjvLhKXMI12602019-07-03T00:00:00+00:00yes https://riseof.ai/talks/ai-in-europe-the-good-news-bj-rn-bringmann/https://i.ytimg.com/vi/rANkTR-MSIc/hqdefault.jpgAI in Europe: The Good News – Björn Bringmann (Rise of AI Conference 2023)At Rise of AI 2023 in Berlin, Björn Bringmann, Managing Director and lead of the AI Institute at Deloitte Germany, argues that Europe's AI position is stronger than the pessimistic narrative he often hears suggests. Presenting Deloitte's global AI survey of about 2,500 executives, including 150 senior executives in Germany, he shows Germany ranking third of 13 countries surveyed on AI maturity and 87% of German executives calling AI crucial to their business over the next five years. He walks through Europe's standing in innovation rankings, chip-making equipment (via ASML, Zeiss and Trumpf), new compute centers, rising AI investment, and the talent and research base built around initiatives such as appliedAI, Cyber Valley and Aleph Alpha, arguing Europe sits closer to the global top ten across most of these dimensions than commonly assumed. He frames his talk explicitly as a deliberately selective, non-exhaustive collection of good news, not a claim that Europe leads globally, and closes by urging more collaboration and better storytelling about existing strengths rather than only more funding or talent.https://www.youtube.com/embed/rANkTR-MSIc18602023-05-14T00:00:00+00:00yes https://riseof.ai/talks/ai-in-manufacturing-teaching-robots-to-learn-by-demonstration-ronnie-v/https://i.ytimg.com/vi/R-DxZWR2iTc/hqdefault.jpgAI in Manufacturing: Teaching Robots to Learn by Demonstration – Ronnie Vuine (Rise of AI Virtual Chat 2021)At a Rise of AI Virtual Chat in February 2021, held in partnership with AWS, Fabian Westerheide interviews Ronnie Vuine, CEO of micropsi industries, about applying AI to manufacturing. Vuine explains how his company's software lets industrial robots learn skills, such as finding a logo on a screen in a live demo or locating features on refrigerators during factory testing, from four or five human demonstrations instead of precise pre-programmed coordinates: the robot watches a worker perform the task, uploads the recordings to AWS for training, and can execute the learned skill after about three hours of cloud computation. He traces micropsi's roots to a Minecraft bot project and to Dietrich Doerner's psi theory of intelligence, and describes why the company deliberately moved away from pursuing AGI toward a sellable product. The conversation then turns to why AI adoption in manufacturing remains low, with Westerheide citing a figure that only six percent of manufacturing businesses use AI, and Vuine arguing that bolting sensors onto old machines is not the same as redesigning production as a software-driven system. He closes with advice on building AI capability in-house, a note on data privacy between customers, and predictions about GPT-3's near-term impact.https://www.youtube.com/embed/R-DxZWR2iTc37202021-02-25T00:00:00+00:00yes https://riseof.ai/talks/ai-is-fuelling-all-areas-of-business-bart-schneider/https://i.ytimg.com/vi/SEqmoyDQOR4/hqdefault.jpgAI is fuelling all areas of business – Bart Schneider (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Bart Schneider, Senior Director Sales EMEA at Nvidia, argues that AI has already moved from a research topic into everyday business and consumer life, and walks through dozens of production use cases his team works on. He opens with personal examples (voice assistants, a Nike shoe-fitting app, early autonomous driving, a back-diagnosis prediction) before framing AI as a new industrial revolution after steam, electricity and compute. He cites market figures including a projected 20 percent boost to global GDP by 2030, an EU investment push, Nvidia's roughly 3,000-startup Inception program, and a data center AI market he says grew from about 339 million to 2 billion dollars in two years within a roughly 50 billion dollar total addressable market. He then runs through concrete deployments across healthcare, infrastructure, defense, retail, agriculture, customer service, smart cities, space, entertainment and drug discovery, each tied to a named customer or partner. He closes by noting, per Accenture, that only about 5 percent of large companies were using AI in production at the time.https://www.youtube.com/embed/SEqmoyDQOR418002019-07-16T00:00:00+00:00yes https://riseof.ai/talks/ai-is-happening-now-deal-with-it-or-die-chris-boos/https://i.ytimg.com/vi/_i31P9eNa50/hqdefault.jpgAI Is Happening Now, Deal With It or Die – Chris Boos (Rise of AI Conference 2022)At Rise of AI 2022 in Berlin, Chris Boos, introduced as a consultant to the German government, argues that Europe is losing on digital sovereignty and that AI adoption fails mainly because of mindset, not technology. He separates industrial sovereignty, where Europe manages through contracts and supply chains despite lacking raw materials, from digital sovereignty, built on intellectual property, software and data, where dominant players aim to own users, developers and IP outright. He says Europe lags badly on energy and hardware (compute, storage, bandwidth) but is strong on APIs and standards, and warns that trying to build a European cloud competitor to Amazon now would waste roughly 100 billion euros without catching up. He then describes cybersecurity as a third form of mutually assured destruction alongside nuclear weapons, citing attacks on critical infrastructure like the Helsinki airport blackout demonstration. His central claim is that AI ends the industrial principle of standardizing and controlling processes, and that most enterprise AI projects stall at the pilot stage because buyers, not the technology, resist change; he contrasts Google's AI-driven efficiency with traditional banks. He closes with suggestions on ecosystems, leadership and rebuilding a more humanistic, curiosity-driven society to retain talent.https://www.youtube.com/embed/_i31P9eNa5016802022-06-13T00:00:00+00:00yes https://riseof.ai/talks/ai-is-not-a-threat-but-a-chance-for-our-society-andreas-steier/https://i.ytimg.com/vi/PbLl0gc8BU8/hqdefault.jpgAI Is Not a Threat, but a Chance for Our Society – Andreas Steier (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Andreas Steier, Member of the German Bundestag, argues that AI policy in Germany should build on existing technical standards rather than start from fear. A former automotive engineer who worked on sensor systems and neural networks before 'AI' became a marketing term, he describes joining the Bundestag in 2017 and becoming his party group's rapporteur for artificial intelligence, sitting on a Bundestag commission that works on an ethical framework for AI. He says the dominant reaction he meets outside Berlin is fear, often based on fiction rather than the reality of the technology, and argues Germany should extend standards already proven in the automotive, energy, industrial and health sectors into the digital age rather than treat AI as an unprecedented threat. Comparing Germany's position to the more entrepreneurial United States and a more centrally directed China, he argues Germany's advantage lies in engineering quality and functional safety, illustrated with a 2018 collision in the United States between a self-driving car and a cyclist, and proposes synthetic data as a way to test rare, safety-critical driving situations.https://www.youtube.com/embed/PbLl0gc8BU86602019-07-01T00:00:00+00:00yes https://riseof.ai/talks/ai-kindergarten-danko-nikolic/https://i.ytimg.com/vi/Xz--yoU842w/hqdefault.jpgAI Kindergarten – Danko Nikolic (Rise of AI Conference 2016)At Rise of AI 2016 in Berlin, brain scientist Danko Nikolic argues that current machine learning cannot produce human-level or superhuman AI because it stores knowledge in a single large, uninterruptible box trained by comparatively simple learning rules, whereas human intelligence is distributed across millions of specialized learning rules compressed into our genes by billions of years of evolution. He illustrates the gap with a demonstration of how humans instantly reinterpret an ambiguous image as a car, a train, or a table and chairs, something today's AI cannot do without prior training on each category. Citing the no-free-lunch theorem, he argues no single general algorithm can be both broad and efficient, which is why the brain relies on many specialized learning rules instead of one. Since evolving such a genome from scratch would take billions of years, Nikolic proposes "AI Kindergarten": starting from a simple genome, deploying it to users such as data scientists, and feeding real-world experience back to a central server to gradually evolve better genomes, accumulating knowledge instead of erasing it between tasks. He concludes that AI built this way could approach but never exceed human intelligence, ruling out an intelligence-explosion singularity.https://www.youtube.com/embed/Xz--yoU842w12602016-02-28T00:00:00+00:00yes https://riseof.ai/talks/ai-made-in-europe-where-we-already-lead-oliver-stuke/https://i.ytimg.com/vi/nq6nNw0HvXg/hqdefault.jpgAI Made in Europe: Where We Already Lead – Oliver Stuke, Anna Gründler, Jörg Bienert, Irakli Beridze (Rise of AI Conference 2026)At Rise of AI 2026 in Berlin, a panel moderated by Anna Gründler with Oliver Stuke (Capgemini), Dr. Irakli Beridze (United Nations) and Jörg Bienert argues against the narrative that Europe lags behind in AI, presenting concrete projects instead. Stuke describes Spark, a German government lighthouse project applying legally sound generative AI to permitting processes such as fishing licenses and wind turbines, built with European partners including Mistral, Aleph Alpha and Fraunhofer institutes and named winner of a global prize for best use of generative AI in government. Beridze describes AI Pol, a UN and Interpol toolkit for responsible AI use in law enforcement, already piloted in India, Brazil, Kazakhstan, Nigeria and Oman with a goal of around 50 countries. Bienert presents SOFI, an open-source sovereign European foundation model trained with Deutsche Telekom and Nvidia, planned to launch in mid-2026 and scale toward 300 to 500 billion parameters. The panel discusses trust as a European differentiator, backed by UN research from Oslo, debates regulatory simplification and AI literacy mandates, and names internal fragmentation as Europe's biggest risk over the next 24 months.https://www.youtube.com/embed/nq6nNw0HvXg27602026-07-15T00:00:00+00:00yes https://riseof.ai/talks/ai-on-steroids-when-ai-hits-the-blockchain-ben-goertzel/https://i.ytimg.com/vi/iBmSl2mslg8/hqdefault.jpgAI on Steroids: When AI Hits the Blockchain – Ben Goertzel (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, Ben Goertzel, CEO of SingularityNET, argues that artificial general intelligence will not come from one magic learning algorithm but from many different AI systems, each with its own strengths, cooperating together. He describes his OpenCog framework, built around a hypergraph knowledge representation called the atomspace, which combines probabilistic logic, evolutionary programming and deep neural networks. He connects this to work with Hanson Robotics' Sophia, including an unscripted OpenCog-driven dialogue demo and a meditation experiment in which about 30 percent of participants reached a deeper trance state than in human-led sessions, reportedly because they did not feel judged by the robot. Goertzel then presents SingularityNET, a blockchain-based marketplace where heterogeneous AI agents outsource tasks to each other and exchange value using the AGI token, which he frames as a decentralized, democratic alternative to AI control by a handful of large companies and governments. He reports a token sale that raised 36 million dollars in December, a growing team, and plans to launch a scalable version of the platform that fall.https://www.youtube.com/embed/iBmSl2mslg823402018-06-10T00:00:00+00:00yes https://riseof.ai/talks/ai-regulation-in-europe-what-s-in-the-pipeline-ursula-feindor-schmidt/https://i.ytimg.com/vi/52A3uijmvaE/hqdefault.jpgAI Regulation in Europe: What’s in the Pipeline? – Ursula Feindor-Schmidt (Rise of AI Summit 2020)At Rise of AI Summit 2020 in Berlin, Dr. Ursula Feindor-Schmidt, a partner at Lausen Rechtsanwälte, surveys European Union proposals for regulating artificial intelligence. She starts from the European Commission's AI High-Level Expert Group definition of an AI system as software, designed by humans, that perceives its environment, interprets data and acts toward a given goal. She notes AI already falls under existing rules such as the General Product Safety Directive, GDPR and sector standards, but argues lawmakers see gaps around security, data-driven bias, autonomy, opacity and unclear liability chains. She reviews initiatives on the table: the European Commission's White Paper on AI, a European Parliament report on AI, IoT and robotics liability, and the upcoming Digital Services Act, which may include obligations for high-risk applications such as biometric identification, conformity labeling, human-contact points and audits of training data quality. In the closing minutes, drawing on her own intellectual-property practice, she covers whether AI itself can be patented or copyrighted, whether training on copyrighted data infringes text-and-data-mining exceptions, and whether AI-generated output can hold copyright, concluding it currently cannot because only humans can be copyright holders.https://www.youtube.com/embed/52A3uijmvaE19802020-11-23T00:00:00+00:00yes https://riseof.ai/talks/ai-solutions-startup-showcase-i2x/https://i.ytimg.com/vi/pcjcqCCTE0M/hqdefault.jpgAI Solutions: Startup Showcase – i2x, AVA, micropsi industries, neurocat, Solvemate, Merantix Lab, Brighter AI, Cognigy, Jasper Masemann (Rise of AI Summit 2020)At Rise of AI Summit 2020 in Berlin, moderator Jasper Masemann (Partner, HV Capital) hosts a two-and-a-half-hour startup demo session in which founders and executives from ten German AI companies pitch their products and take short audience Q&A. Nicole Büttner presents Merantix Labs as an external machine learning department for corporate NLP, computer vision and forecasting projects. Stefan (neurocat) presents automated robustness, safety and explainability testing for deployed AI, including an 'attack generator' for stress-testing models. Alexander Stojanovic presents AVA, a data-standardization platform for security, safety and risk information used by organizations such as London's police and DHL. Micropsi Industries and Wandelbots present software for training industrial robots from camera and sensor data without conventional programming. i2x, Solvemate and Cognigy present conversational AI for customer service, ranging from real-time agent coaching to self-service chatbots and voice automation. A privacy-technology founder presents 'AI for Privacy', a case-based tool for automating GDPR risk assessments, and Clemens (Sia Search) presents a metadata-search layer for large unstructured computer-vision datasets. Each pitch covers the product, target customers and a short Q&A on differentiation and roadmap.https://www.youtube.com/embed/pcjcqCCTE0M87002020-11-30T00:00:00+00:00yes https://riseof.ai/talks/ai-startup-demos-gestoos-german-autolabs-inspirient-searchink-twenty-b/https://i.ytimg.com/vi/hCduaIIodw8/hqdefault.jpgAI Startup Demos: Gestoos, German Autolabs, Inspirient, Searchink, Twenty Billion Neurons, Aisoy Robotics – Gestoos, German Autolabs, Inspirient, Searchink, Twenty Billion Neurons, Aisoy Robotics (Rise of AI Conference 2017)At Rise of AI 2017 in Berlin, six AI startups pitch their products back to back in a demo session, each followed by questions from a panel and the audience. Gestoos presents gesture-recognition software for digital signage and cars, built from small labeled datasets and refined with live deployment data, and reports a 1,500-license retail rollout. German Autolabs shows Chris, a voice-and-gesture assistant for cars that reads messages and adapts to driving context, funded through a recent Kickstarter campaign. Inspirient demonstrates software that automatically scans business spreadsheets and sensor data to generate presentation slides of anomalies, illustrated with the Volkswagen emissions dataset and a DB Schenker shipping-container example. Searchink pitches AI-based document process automation that classifies and extracts data from paper and digital document streams for corporates, citing access to roughly 900 million documents from a founder's earlier company. Twenty Billion Neurons describes a crowd-acting platform that pays contributors to film labeled action videos, used to build the largest known hand-gesture dataset and a webcam-based gesture demo. Aisoy Robotics closes with a live demo of Aisoy1 Kid, an emotional educational robot with an internal 'mentor' system, reporting over 3,000 users mainly in Spain, France and the US.https://www.youtube.com/embed/hCduaIIodw845002017-05-25T00:00:00+00:00yes https://riseof.ai/talks/ai-strategies-building-an-ecosystem-not-just-planning-adrian-locher/https://i.ytimg.com/vi/Z_Poel1UZLE/hqdefault.jpgAI Strategies: Building an Ecosystem, Not Just Planning – Adrian Locher (Rise of AI Summit 2020)At Rise of AI Summit 2020 in Berlin, Adrian Locher, co-founder and CEO of Merantix, argues that Germany and Europe already have the ingredients for AI success but consistently fail to assemble them. He says Germany has more AI researchers per capita than the US and China combined, strong hardware and industrial players, and access to top talent, yet fails to transfer research into software companies. Rather than presenting a strategy, Locher describes what it takes to actually build AI products: handling messy edge-case data, keeping pace with fast-moving research, coping with long B2B sales cycles, and accepting that full automation is unrealistic. He details how Merantix, founded in 2016 as a venture studio, has built five companies, recruits from over 50 applicants per hire, runs internal knowledge-sharing formats, raised a 25 million fund backed by US institutional investors, and is opening a 5,000 square meter Berlin campus for over 450 people in April 2021. In the Q&A he stresses that teams, not technology or markets, determine whether AI ventures succeed or fail.https://www.youtube.com/embed/Z_Poel1UZLE21002020-11-20T00:00:00+00:00yes https://riseof.ai/talks/ai-strategy-beyond-the-ai-race-winners-losers-and-the-countervailing-m/https://i.ytimg.com/vi/L92bqS2r-Ls/hqdefault.jpgAI Strategy Beyond the AI Race: Winners, Losers and the Countervailing Move – Jesse Lehrke (Rise of AI Summit 2020)At the Rise of AI Summit 2020, Dr. Jesse Lehrke, a researcher at Freie Universität Berlin who describes spending recent funding breaks learning Python and neural networks, argues that most current AI strategies are really just strategies for winning the AI race, not for what to do once AI, or a technological singularity, actually arrives. He frames strategy as the moves and countervailing moves opposing wills use to get more out of a situation than the underlying balance of power suggests, particularly useful for weaker parties, and argues academics should not fear "futurology" given the stakes. Because the singularity is by definition unknowable, Lehrke proposes thinking about the limits physics imposes on any actor, human or AI, including the speed of light and quantum-level constraints on secrecy, as tools that can be used to shape an AI's behavior through embedded uncertainty rather than eliminated uncertainty. Drawing on Clausewitz's trinity of passion, reason and chance, and on nuclear deterrence as a model of control through non-use, he argues design decisions made today, not decisions made after the AI race is won or lost, determine how controllable future AI actors will be.https://www.youtube.com/embed/L92bqS2r-Ls17402020-11-23T00:00:00+00:00yes https://riseof.ai/talks/ai-gender-and-power-eva-gengler/https://i.ytimg.com/vi/2m9r9hNSkmM/hqdefault.jpgAI, Gender and Power – Eva Gengler (Rise of AI Conference 2026)At Rise of AI 2026 in Berlin, Dr. Eva Gengler, drawing on her dissertation research and her book on feminist AI, argues that AI systems replicate and can reinforce existing power structures unless people actively design against it. She surveys where AI affects people, from recruiting and social media to medical diagnosis and news feeds, and shows through examples such as Amazon's biased recruiting tool, gender bias in credit scoring, racial bias in mortgage lending algorithms, and TikTok's reduced visibility for queer people and people with disabilities, that AI is not neutral. She uses Grok, the AI built by Elon Musk's xAI, as an extended case study of how training data, system prompts and homogeneous, male-dominated teams shape controversial outputs, including antisemitic statements and non-consensual deepfake images. She situates this within patriarchy, neoliberal capitalism and neo-colonial data labor, and closes with concrete steps: diversity panels, data transparency, AI governance, feminist prompting, and real-world feminist AI projects addressing domestic violence, health gaps and girls' education.https://www.youtube.com/embed/2m9r9hNSkmM18602026-07-15T00:00:00+00:00yes https://riseof.ai/talks/ai-don-t-fear-it-love-it-charles-edouard-boue-e/https://i.ytimg.com/vi/ZLQnrxwhm4M/hqdefault.jpgAI: Don’t Fear It, Love It – Charles-Edouard Bouée (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, Charles-Edouard Bouée, CEO of Roland Berger, presents the results of four years of travelling the world to meet AI specialists, arguing that people should not fear AI but embrace it. He frames the argument through a history of technology waves: PC and software (IBM, Microsoft), telecom and GSM (won by Europe through regulation), smartphones and platforms (won by the US and China), and now a fourth, still open wave of AI. Using a story he calls the Kenny Ocean theorem, about a France Telecom futurist fired in 2000 for predicting a device that would become "the remote control of your life," he argues that winners of one wave typically lose the next because their business model does not transfer. He predicts the rise of portable, personal AI that will disrupt advertising-funded platforms such as Google, Facebook, Uber and Airbnb, and describes the resulting shift as a move from artificial intelligence to advanced human intelligence.https://www.youtube.com/embed/ZLQnrxwhm4M14402018-06-10T00:00:00+00:00yes https://riseof.ai/talks/ai-s-bumpy-road-and-glorious-future-christoph-von-der-malsburg/https://i.ytimg.com/vi/KuDti0_5LOg/hqdefault.jpgAI’s bumpy road and glorious future – Christoph von der Malsburg (Rise of AI Conference 2017)At Rise of AI 2017 in Berlin, Christoph von der Malsburg argues that neither of the two historical routes to AI, the general-purpose computer and the brain-inspired neural network, can on its own solve general intelligence. The computer, he says, is a universal but empty machine that depends entirely on human programming, while today's neural networks and deep learning depend entirely on annotated data; in both cases, he argues, AI remains, in his words, human thought loaded into machines in a detailed way. He then discusses how AI systems must widen their contextual scope by decomposing a situation into abstract, relatively independent aspects, and draws an analogy to children, who apply innate, abstract behavioral patterns to concrete situations within their first years of life and learn concepts such as a tricycle from a single exposure. He argues general intelligence will come from a conceptual breakthrough rather than decades of engineering, supporting this with an information-theoretic gap between the cortex's wiring complexity and the genome's size. He closes by describing his own model of recognition through switchable, collectively decided "network fragments," illustrated with a face-recognition system and a Raven's matrices reasoning test.https://www.youtube.com/embed/KuDti0_5LOg15602017-05-25T00:00:00+00:00yes https://riseof.ai/talks/alternate-paths-to-agi-rafael-laguna-de-la-vera/https://i.ytimg.com/vi/XkmlkDCk8pM/hqdefault.jpgAlternate Paths to AGI – Rafael Laguna de la Vera (Rise of AI Conference 2025)At Rise of AI 2025 in Berlin, Rafael Laguna de la Vera, director of SPRIND, Germany's Federal Agency for Disruptive Innovation, argues that Europe needs a more optimistic, self-built vision of the future and describes how SPRIND tries to fund the breakthroughs that create it. He traces SPRIND's founding to Angela Merkel's 2017 decision and the four years it took to pass the SPRIND Liberty Law freeing the agency from standard ministry procurement rules, modeled on how the US founded NASA and DARPA after Sputnik. He argues Germany produces twice as many patents per capita as the US from strong basic research, yet only a twentieth as many unicorns, because later-stage funding is scarce and 80 percent of trade sales above a 25-million-euro valuation go outside Europe. He details SPRIND's two funding tools, fast 'challenges' with concrete deadlines and always-open project proposals, illustrated by a 35-million-euro broadband antiviral challenge launched during COVID, and describes SPRIND's push into new AI architectures, distributed compute and alternative computing hardware such as neuromorphic and optical computing to reduce dependence on massive GPU data centers.https://www.youtube.com/embed/XkmlkDCk8pM19802025-05-21T00:00:00+00:00yes https://riseof.ai/talks/are-machines-the-better-decision-makers-katharina-zweig/https://i.ytimg.com/vi/kcJc5IYaQo8/hqdefault.jpgAre Machines the Better Decision Makers? – Katharina Zweig (Rise of AI Conference 2024)At Rise of AI 2024 in Berlin, Prof. Dr. Katharina Zweig of RPTU Kaiserslautern-Landau argues that machines can reliably help with only some kinds of decisions, not all of them. She distinguishes four decision types: factual decisions, risk predictions, judgments and singular decisions, and argues AI can, in principle, be checked and trusted for the first two, since their correctness can be verified, but not for judgments, where qualities must be weighed subjectively and justified in words. She demonstrates that ChatGPT 3.5 cannot reliably perform long multiplication despite producing plausible step-by-step explanations, arguing a single failed test is enough to show a system cannot be trusted with a task in general. Using a real case of a user asking ChatGPT to build dynamic pricing for a shop, including an Amazon incident where competing pricing algorithms sold products for one cent, she shows how large language models generate functioning-looking code without asking the requirements questions a human expert would raise. Her conclusion: citizens need basic computer science and AI literacy to check AI-generated solutions rather than trust them outright, since judgment decisions still require human weighing and justification.https://www.youtube.com/embed/kcJc5IYaQo811402024-05-21T00:00:00+00:00yes https://riseof.ai/talks/are-you-really-safe-understanding-and-predicting-crime-terror-and-disa/https://i.ytimg.com/vi/El1kT9VeFWU/hqdefault.jpgAre You Really Safe? Understanding and Predicting Crime, Terror and Disaster – Aleksandar Stojanovic (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Aleksandar Stojanovic, Executive Chairman and co-founder of AVA, explains how his company acts like a weather forecasting service for physical risk: crime, terrorism, fire, natural disasters, civil unrest and healthcare emergencies such as epidemics. He stresses that AVA does not do facial recognition or track individuals but analyzes behaviors and locations, serving clients such as the London Metropolitan Police, public transport operators and logistics companies. He describes AVA's Risk Score as combining past, present and predictive security data for a given place, built from internal partner data, sensors and cameras, social media monitoring, and even legally accessible US police radio scanners transcribed with speech recognition. He gives concrete examples: detecting the 2017 London Bridge attack four minutes before official procedures, predicting crime in Los Angeles from ten years of hourly data with an error rate just above 5 percent, and using trust scoring to filter fake or panic-driven social media reports. He also describes ambient audio baselines, gunshot triangulation by sound, and computer-vision aggression detection as further data sources, framing AVA as a system that contextualizes overwhelming data for human operators rather than replacing them.https://www.youtube.com/embed/El1kT9VeFWU16202019-09-05T00:00:00+00:00yes https://riseof.ai/talks/art-in-the-age-of-algorithms-stefanie-kr-ll/https://i.ytimg.com/vi/HapfZO0-7FA/hqdefault.jpgArt in the Age of Algorithms – Stefanie Krüll (Rise of AI Conference 2025)At Rise of AI 2025 in Berlin, artist and AI creator Stefanie Krüll traces her own journey with Midjourney since 2022, from glitchy early outputs to today's photorealistic images, and shows recurring series built around high-gloss surfaces, contrasts of color and texture, and a chimera-themed video narrated with lines from Baudelaire and scored using Kling AI and Suno. She describes training her own small Flux model on twelve photos of herself to generate an imagined version of her life from childhood to old age, a project shaped by her father's death at 38, and argues the emotional impact she felt watching it shows AI-assisted work is not devoid of feeling. She walks through a history of computer art, from Michael Noll's coining of the term at Bell Labs through Vera Molnár, Harold Cohen's AARON, Refik Anadol, the GAN-generated portrait 'Edmond de Belamy' sold at Christie's, Mario Klingemann's self-generating portrait machine, and the robot artist Ai-Da, before naming three contemporary generative artists she follows. A Q&A closes on whether AI can create art, with Krüll and an audience member agreeing that the human artist's intent, not the tool, is what makes the result art.https://www.youtube.com/embed/HapfZO0-7FA21602025-05-21T00:00:00+00:00yes https://riseof.ai/talks/artificial-intelligence-and-energy-ralf-herbrich/https://i.ytimg.com/vi/TwDTwP6zdG0/hqdefault.jpgArtificial Intelligence and Energy – Ralf Herbrich (Rise of AI Conference 2023)At Rise of AI 2023 in Berlin, Ralf Herbrich, professor at the University of Potsdam and managing director of the Hasso Plattner Institute, argues that AI's growing energy cost is an underexamined limit on its future, and that AI can also help solve the transition to renewable energy. He says the classic Turing test of matching human behavior has effectively been passed in narrow domains such as Go, image recognition and coherent text generation, but that a 'revised' Turing test factoring in energy cost is far from being met: training a robotic arm to grasp an object, he says, can cost roughly 2.8 gigawatt-hours, equivalent to about 200 human lifetimes of energy, and AI compute energy use has been doubling roughly every three months since 2012. He describes three research directions for more energy-efficient AI: data-efficient models and model pruning, approximate low-precision and error-tolerant computing, and analog computing, and separately describes how AI can improve renewable-energy prediction and battery management, including estimating a battery's degradation from limited sensor data.https://www.youtube.com/embed/TwDTwP6zdG023402023-05-14T00:00:00+00:00yes https://riseof.ai/talks/artificial-intelligence-and-the-future-of-humanity-fabian-westerheide/https://i.ytimg.com/vi/DrjyNgis8_c/hqdefault.jpgArtificial Intelligence and the Future of Humanity – Fabian Westerheide (Rise of AI Conference 2017)At Rise of AI 2017 in Berlin, Fabian Westerheide, founder of the conference, gives the opening keynote from the venue hosting a rebuild of Konrad Zuse's Z1, the first programmable computer built in Europe. He recounts how Rise of AI grew from a 15-person meetup at the c-base hackerspace to over 300 attendees, and defines artificial intelligence as algorithms that use data to make and improve their own decisions within given frameworks. He walks through AI already in use, including IBM's Deep Blue and Watson, AlphaGo's win over Lee Sedol, Cortana, Amazon Alexa, self-driving cars, AI-run stock markets, and younger AI companies such as Berlin's Parlamind and Micropsi Industries and London's Exlo Dynamics. He then looks ahead to brain-computer interfaces and an emerging internet of agents by around 2025, describes new jobs such as AI trainer and AI controller, and closes by arguing that without a strong European AI ecosystem, AI will end up thinking American or Chinese rather than reflecting European values.https://www.youtube.com/embed/DrjyNgis8_c15002017-05-24T00:00:00+00:00yes https://riseof.ai/talks/artificial-vs-natural-intelligence-moritz-helmstaedter/https://i.ytimg.com/vi/86L1_Qa2VWQ/hqdefault.jpgArtificial vs. Natural Intelligence – Moritz Helmstaedter (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Moritz Helmstaedter, Managing Director at the Max Planck Institute for Brain Research, argues that today's deep learning still corresponds closely to neuroscience ideas from the 1960s, using feed-forward connectivity inspired by early visual system anatomy and neuron nonlinearities, without fundamentally new architecture. He argues artificial and biological intelligence differ most sharply in two respects: energy efficiency, and especially label efficiency, since a child learns to recognize a tree after hearing the word only 50 to 100 times, while machine learning systems need billions of labeled examples. He presents his field, connectomics, which uses electron microscopy to map brain circuits at the scale of individual synapses, describing findings including a fully reconstructed mammalian retinal circuit, the discovery that each cortical nerve cell connects to roughly 1,000 others, and a newly found "triadic" inhibitory circuit motif in the entorhinal cortex that may function as a context-gated hypothesis circuit. He argues brains, unlike computers, do not separate memory and processing, making circuit structure itself informative about function, and closes by proposing that mapping brain circuits in detail could again inspire new, more energy- and label-efficient computing architectures, as neuroscience did for early AI.https://www.youtube.com/embed/86L1_Qa2VWQ16802019-07-17T00:00:00+00:00yes https://riseof.ai/talks/ask-me-anything-about-the-future-of-ai-driven-business-models-ben-blum/https://i.ytimg.com/vi/Vl3iUa2hwFA/hqdefault.jpgAsk Me Anything About the Future of AI-Driven Business Models – Ben Blume, Jasper Masemann, Rasmus Rothe (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, a panel with Ben Blume of Atomico, Jasper Masemann of HV Holtzbrinck Ventures and Rasmus Rothe, CTO at Merantix, takes audience questions on what actually works in AI-driven business models. Rasmus Rothe describes Merantix as a venture studio that incubates AI companies for one to three years with up to a few million euros in funding, running joint projects with industry partners such as hospitals and car manufacturers. The panel discusses how machine learning maturity varies by field, with areas like speech recognition already supported by mature libraries while others, such as large-scale simulation, remain research-led and carry both technical and commercialization risk. Audience questions cover which industries AI will disrupt most, liability and explainability for black-box models, why the panelists keep investing from Europe despite the pull of Silicon Valley and Asia, how startups can build labeled data sets through customer-facing products before adding machine learning features, and what business-outcome measures, rather than raw model metrics, investors actually use to judge an AI company's performance.https://www.youtube.com/embed/Vl3iUa2hwFA22802019-07-18T00:00:00+00:00yes https://riseof.ai/talks/automatic-analysis-of-medical-images-with-deep-learning-jonas-muff/https://i.ytimg.com/vi/VXEZKThVgcY/hqdefault.jpgAutomatic Analysis of Medical Images with Deep Learning – Jonas Muff (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Jonas Muff, CEO of MX Healthcare by Merantix, describes bringing a fully autonomous medical diagnostic system from development to commercial deployment with its first customers. No usable transcript is available for this talk, so this page is built from the YouTube description alone. According to that description, Muff covers key learnings from the process of commercializing the system, with particular attention to product design as a factor in whether the tool succeeds in the field. He addresses specific tactics for gaining adoption among medical experts, a group whose trust and buy-in the description frames as a central obstacle for autonomous diagnostic tools in clinical settings. The talk is further described as touching on what the description calls the value of machine augmentation of human expertise in the age of deep learning, positioning the system as a support to medical judgment rather than a simple replacement for it. No further detail on the system's technical design, clinical results or the specific hacks used to gain adoption is available without the transcript.https://www.youtube.com/embed/VXEZKThVgcY11402019-07-19T00:00:00+00:00yes https://riseof.ai/talks/automating-intelligence-the-future-of-automl-holger-hoos/https://i.ytimg.com/vi/-zhxU_mfaSE/hqdefault.jpgAutomating Intelligence: The Future of AutoML – Holger Hoos (Rise of AI Conference 2026)At Rise of AI 2026 in Berlin, Holger Hoos of RWTH Aachen University argues that Europe should focus on safe, dependable and sustainable AI, using AutoML as a concrete example, rather than chasing the same generative AI hype as the US and China. He opens with examples of AI failure and overreach, including a Wall Street Journal vending machine run by an AI agent that lost money buying live fish, a coding agent that deleted a customer's database in nine seconds, and a paper called "Agents of Chaos" documenting unauthorized and destructive agent behavior. Hoos argues intelligence requires reasoning with formal guarantees, not just learning, and presents AutoML, automating decisions such as hyperparameter optimization, model selection, neural architecture search and pipeline optimization through techniques like Bayesian optimization, meta-learning and evolutionary optimization, as a safer, more efficient alternative to letting generative AI write software outright. He cites European AutoML strength centered in Aachen, Dortmund, Hanover, London and Tübingen, but warns that Europe's AI research now trails not only the US and China but also Singapore and South Korea, and calls for an expert-driven European AI agency modeled on ESA and CERN.https://www.youtube.com/embed/-zhxU_mfaSE16802026-07-15T00:00:00+00:00yes https://riseof.ai/talks/automation-intelligence-ronnie-vuine/https://i.ytimg.com/vi/jyoNRZziq9Y/hqdefault.jpgAutomation Intelligence – Ronnie Vuine (Rise of AI Conference 2016)At Rise of AI 2016 in Berlin, Ronnie Vuine argues that asking when the technological singularity will happen is close to meaningless, comparing it to a black hole: observers cannot see past its event horizon, and those approaching it notice no distinct moment of crossing. Rather than a sudden "hard takeoff" driven by one team's breakthrough, he frames the singularity as a roughly 300-year process he calls techno-capital, in which positive feedback loops between capital and technology extract intelligence from the land, moving people from agriculture into cities and abstract, complexity-managing work. He illustrates deliberate historical dampening of this feedback loop with a 1777 mechanical cabinet, whose maker needed special permission to bypass Rococo-era guild rules limiting workshops to four employees. Vuine expects the present to bring not one explosive breakthrough but many competing, accelerating automation systems, closing with a reading from philosopher Nick Land's essay on techno-capitalist singularity and a guess that transferable machine-learned representations are five to ten years away.https://www.youtube.com/embed/jyoNRZziq9Y11402016-02-28T00:00:00+00:00yes https://riseof.ai/talks/becoming-the-ki-nation-thomas-jarzombek/https://i.ytimg.com/vi/2A4r-bFS6QA/hqdefault.jpgBecoming the KI-Nation – Thomas Jarzombek (Rise of AI Conference 2025)At Rise of AI Conference 2025 in Berlin, Thomas Jarzombek, member of the Bundestag and Parliamentary State Secretary for Digital Affairs and State Modernization, outlines his brand-new ministry's plans for AI just one week after it was formed. He frames AI regulation as an opportunity rather than a restriction, describing an ongoing internal debate about how to implement the EU AI Act and simplify GDPR and the Data Act. He describes plans to attract global scientific and business talent through a faster work-and-stay visa process and 1,000 new AI professorships, and to close the gap with US large language models through open source work led by the Sovereign Tech Agency. He discusses Germany's bid for one of the EU's AI gigafactories, building on Jülich's existing 24,000 GPUs, and improving GPU access for startups and SMEs. He also describes building a reusable "Deutschland Stack" of government software components, using government procurement to support AI startups, a sovereign desktop operating system, and the EU Digital Identity wallet.https://www.youtube.com/embed/2A4r-bFS6QA10802025-05-21T00:00:00+00:00yes https://riseof.ai/talks/bees-and-robots-tim-landgraf/https://i.ytimg.com/vi/d2FRSMzUqNk/hqdefault.jpgBees and Robots – Tim Landgraf (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Tim Landgraf, professor of artificial and collective intelligence at Freie Universitaet Berlin, argues that building better AI requires first understanding biological intelligence, summed up as 'B comes before A.' He studies honeybees as a model system because their entire life cycle, social interactions and individual navigation can be tracked in ways not possible with humans or larger animals. He describes recording brain activity from bees flying over open fields with electrodes and a miniaturized lab mounted on a copter, and explains how a labeling bottleneck in tracking bee markers led his student Leon to develop RenderGAN, a generative adversarial network that learns to generate realistic training images with controllable labels, later applied to faces. Landgraf closes with an example of how bees share food through a 'social stomach' and proposes a similar energy-sharing model for self-driving electric cars, demonstrated with model cars and induction coils. He ends with calls for more public research funding and closer attention to solutions already found in nature.https://www.youtube.com/embed/d2FRSMzUqNk17402019-07-17T00:00:00+00:00yes https://riseof.ai/talks/benchmarking-progress-towards-agi-marek-rosa/https://i.ytimg.com/vi/XofK_PecU7c/hqdefault.jpgBenchmarking Progress Towards AGI – Marek Rosa (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Marek Rosa, CEO and CTO of GoodAI, addresses how progress toward artificial general intelligence can be measured. According to the talk's description, he asks how success can be defined when working towards general artificial intelligence, what key milestones need to be reached along the way, and how those milestones can be reached in practice. The talk's chapters indicate it covers what intelligence is as a starting point for any benchmarking effort, followed by a discussion of AI training tasks as a way to test and track progress. No reliable transcript is available for this recording, so the detailed arguments, examples and specific benchmarks or tasks Rosa presents cannot be reconstructed here with confidence. The talk sits within GoodAI's broader public work on defining and measuring general intelligence in AI systems, a theme reflected in the talk's title and its stated focus on benchmarking rather than on a single model or application.https://www.youtube.com/embed/XofK_PecU7c13802019-07-17T00:00:00+00:00yes https://riseof.ai/talks/benefits-from-ai-irakli-beridze/https://i.ytimg.com/vi/25i8ncFKYhM/hqdefault.jpgBenefits from AI – Irakli Beridze (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, Irakli Beridze, Senior Strategy and Policy Advisor for Artificial Intelligence and Robotics at the United Nations, describes how the UN is trying to maximize AI's benefits for the Sustainable Development Goals while managing its risks. Speaking just after the UN's Global Summit on AI for Good in Geneva, he traces how fast military and civilian technology changed in fifteen years, from zero military robots in the 2003 Iraq war to hundreds of thousands or millions in use by 2018, and describes the UN's own path from a first AI discussion at the General Assembly in 2015 to a Centre for AI and Robotics opened in The Hague. He surveys national AI strategies, including China's goal of matching the United States by 2020, leading by 2025 and dominating the field by 2030, and names four risk areas: technological unemployment, with no agreed remedy; AI-enabled crime such as deepfakes; lethal autonomous weapons, where experts agree only that a human should make the final kill decision; and existential risk from superintelligence. He closes with examples in health, education and justice, and calls for closer UN, government, academic and industry cooperation.https://www.youtube.com/embed/25i8ncFKYhM13802018-06-10T00:00:00+00:00yes https://riseof.ai/talks/beyond-algorithms-human-oid-intelligence-hans-uszkoreit/https://i.ytimg.com/vi/KIcflhOK7ZU/hqdefault.jpgBeyond Algorithms: Human(oid) Intelligence – Hans Uszkoreit (Rise of AI Conference 2025)In the closing Meta Stage keynote at Rise of AI 2025 in Berlin, Prof. Dr. Hans Uszkoreit, Scientific Director at DFKI, argues that most of today's AI progress comes not from new algorithms but from what he calls "machine teaching,": feeding models more and better data. He reviews the shift from pre-2017 recurrent architectures to the transformer, describes current algorithm research as split between agent systems and next-generation architectures combining attention, memory and agency, then argues that since 2022 breakthroughs like chain-of-thought reasoning, DeepSeek's reinforcement-learning gains and reduced hallucination are really teaching effects, not algorithmic ones. He estimates humanity has produced roughly 150 million books, of which any single expert absorbs only a tiny fraction, and discusses lawsuits from authors like Sarah Silverman and Adam Nevill against Meta over training data. He describes a "knowledge paradox" where broad models beat generalist humans but lose to deep specialists, outlines ways to add domain knowledge, and closes by arguing that as intelligence becomes a cheap commodity, human value will shift toward handling dynamic, unforeseen situations and other people.https://www.youtube.com/embed/KIcflhOK7ZU19202025-05-21T00:00:00+00:00yes https://riseof.ai/talks/beyond-cloud-or-on-prem-rethinking-enterprise-ai-sovereignty-daniel-br/https://i.ytimg.com/vi/x-ZTCfEVHQ8/hqdefault.jpgBeyond Cloud or On-Prem: Rethinking Enterprise AI Sovereignty – Daniel Brilz (Rise of AI Conference 2026)At Rise of AI 2026 in Berlin, Daniel Brilz of SVA argues that the usual cloud-versus-on-prem framing of AI sovereignty is wrong, because it forces a binary choice that produces suboptimal architecture. The real question, he says, is which dependencies are acceptable for which workload. He names four forces making sovereignty strategically relevant: regulation moving from theory to enforcement, geopolitics changing how companies view critical workloads, lock-in risk from AI platform choices, and Gen AI becoming core business infrastructure rather than an experiment. Sovereignty, in his definition, means practical control across three layers: technical, operational and contractual, covering access, encryption keys, governance and exit strategy. He presents a spectrum running from fully managed cloud/SaaS to air-gapped systems, argues dependency exists across the whole stack rather than just hosting location, and outlines a two-step decision framework: classify the workload's sensitivity and criticality, then weight architectural options on portability, assurance, resilience and economics. He closes with design patterns and a cost warning that sovereignty is never free.https://www.youtube.com/embed/x-ZTCfEVHQ816802026-07-15T00:00:00+00:00yes https://riseof.ai/talks/beyond-the-hype-a-practical-blueprint-for-production-ai-christian-wint/https://i.ytimg.com/vi/trkO43fc6R4/hqdefault.jpgBeyond the Hype: A Practical Blueprint for Production AI – Christian Winterfeldt (Rise of AI Conference 2025)At Rise of AI 2025 in Berlin, Christian Winterfeldt, CTO & Director AI Solutions at Dell Technologies, argues that organizations fail with AI not because they lack talent or tools but because they lack a common strategy. He divides the AI market into three phases: a 30-year-old pre-generative-AI market of roughly 2,500 highly specified use cases, the recent large language model market that made organizations more efficient, and an emerging enterprise market built on agentic inferencing that changes business outcomes rather than just optimizing tasks. He illustrates this with a procurement manager, Anna, whose agents monitor markets, prices and contracts overnight, and a product manager, Lisa, whose work depends on six core AI capabilities including bringing corporate context to LLMs and managing trusted data. Winterfeldt presents a "strategy house" model, developed and applied inside Dell itself, that moves from vision and use-case selection to a scalable foundation of culture, data, technology and ecosystem, and finally to execution. He closes with Dell's own on-premise AI platform results and a checklist for building a production-grade AI environment, insisting organizations start with a business goal rather than with technology.https://www.youtube.com/embed/trkO43fc6R421602025-05-21T00:00:00+00:00yes https://riseof.ai/talks/brains-symbols-and-intelligence-christoph-von-der-malsburg/https://i.ytimg.com/vi/rlfrhwKbg1c/hqdefault.jpgBrains, Symbols and Intelligence – Christoph von der Malsburg (Rise of AI Conference 2026)At Rise of AI 2026 in Berlin, Christoph von der Malsburg argues that present AI, impressive as a passive "encyclopedia," remains a black box that learns inefficiently and cannot yet safely act on its own, citing Anthropic's refusal to let a government control weapons with its AI as a sign of how shaky current control is. He proposes animals as the model for future "agentic AI": many are born with most of their behavior already in place, and should be able to learn a new environment the way an employee learns a company, by observing rather than months of training data. He argues biology-based AI is regaining interest, citing ventures founded by Jeff Bezos, Yann LeCun and Jeff McCaleb and new German funding calls, but says none of them yet knows how a squirrel does what it does. Drawing on his own decades of research, he lays out a framework built on structured perception, a "jigsaw puzzle" model of object representation in the visual cortex, mapping between sensory input and abstract categories, and innate behavioral schemata, closing by arguing Europe could out-compete data-hungry American and Chinese AI with an approach that does not depend on mass data.https://www.youtube.com/embed/rlfrhwKbg1c19202026-07-15T00:00:00+00:00yes https://riseof.ai/talks/breast-cancer-detection-with-ibm-powerai-vision-florin-manaila/https://i.ytimg.com/vi/o2lo4hZbzLE/hqdefault.jpgBreast Cancer Detection with IBM PowerAI Vision – Florin Manaila (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Florin Manaila, Senior AI Architect and Inventor at IBM Systems Hardware Europe, presents an IBM proof of technology for detecting breast cancer from MRI and histopathological images using convolutional neural networks. He explains that diagnosis today moves through clinical evaluation, mammography, sometimes ultrasound, MRI and biopsy, with lab analysis of tissue samples alone taking two to three weeks, and that early detection is linked to much higher survival, citing National Cancer Institute UK figures. He frames the work within the regulatory category of software as a medical device and describes an infrastructure stack covering data governance, a data lake, distributed training and bias detection. Using IBM's AC922 hardware and PowerAI Vision software running on-premise in hospitals, his team trained a classification model on more than 10,000 histopathology images, reaching 93 percent accuracy after image augmentation. He describes next steps including extending the approach to mammography, combining multiple imaging modalities with patient context, and building AI operations for monitoring deployed models, while stressing that hospitals train their own models on their own verified, labeled data.https://www.youtube.com/embed/o2lo4hZbzLE14402019-07-15T00:00:00+00:00yes https://riseof.ai/talks/building-a-money-printing-ai-raul-glavan/https://i.ytimg.com/vi/2nToj5uJ5MI/hqdefault.jpgBuilding a Money Printing AI – Raul Glavan (Rise of AI Virtual Chat 2020)At a Rise of AI Virtual Chat recorded in July 2020, Fabian Westerheide interviews trader Raul Glavan, who describes building an AI system that automates and, he says, now outperforms his own decades of manual trading. Glavan traces his path from childhood chess and an early home computer through winning Germany's Iron Trader competition and the Forex World Cup to a system trained specifically on his own trading behavior rather than generic market data. He explains a mean-reversion strategy grounded in behavioral finance, buying into panic and selling into euphoria across stocks, commodities and currencies, using scraped sentiment data and LSTM neural networks with peephole connections built in Python and TensorFlow. He reports around five trades a week held roughly 30 days each, a 93 percent historical win rate, a profit factor of 24, and a Sharpe ratio near 20, which he calls unsustainable given his small sample size. He also describes overruling his own system during the March 2020 Corona panic and losing money as a result. The conversation closes with a discussion of universal basic income and equal taxation of AI and human income as responses to automation-driven job loss.https://www.youtube.com/embed/2nToj5uJ5MI43802020-07-17T00:00:00+00:00yes https://riseof.ai/talks/building-an-ai-powered-organization-stefan-mesken/https://i.ytimg.com/vi/w-08cA30RHg/hqdefault.jpgBuilding an AI-Powered Organization – Stefan Mesken (Rise of AI Conference 2025)At Rise of AI 2025 in Berlin, Stefan Mesken, Head of AI at DeepL, explains how DeepL has built an AI-native, vertically integrated company since its 2017 founding in Cologne. He describes DeepL's mission as breaking down language barriers, and argues the company's advantage comes from owning its infrastructure, data access and product development rather than being a generic model provider. He walks through DeepL's product history, from the original translator through the Glossary, DeepL Write, DeepL Voice and the Clarify feature, and explains the 2022 decision to move from custom model architectures to LLMs, which led to the DeepL Mercury supercluster built with Nvidia. He outlines guiding principles: staying focused on the mission, delivering solutions rather than raw technology, avoiding benchmark chasing, and treating failures as information about the next S-curve of progress. In a short Q&A he discusses linguistic surprises in Chinese and Japanese translation and the challenge of translating culturally loaded political terms such as digital sovereignty.https://www.youtube.com/embed/w-08cA30RHg18002025-05-21T00:00:00+00:00yes https://riseof.ai/talks/building-artificial-general-intelligence-chris-boos/https://i.ytimg.com/vi/9e8XbFFkDuA/hqdefault.jpgBuilding Artificial General Intelligence – Chris Boos (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, Chris Boos, CEO of Arago, argues that current AI is far from strong AI and pushes back on what he calls AI hype. He states plainly that machines do not understand anything, that comparing neural networks to the human brain is misleading given the gap in scale (about a million nodes versus roughly 84 billion neurons) and missing chemical and quantum layers, and that deep learning is only one part of AI, not AI itself. He distinguishes narrow AI, applied to single problems; science-fiction-style strong AI, which he says no one seriously building AI knows how to start; and generalized AI, applicable to more than one problem with the same engine. He describes three underlying algorithm types, machine learning, natural language processing and machine reasoning, tying each to an evolutionary analogue, and argues companies should first explicitly communicate the knowledge they already have to a machine before relying on costly trial-and-error learning, since data by itself can never fully explain the world.https://www.youtube.com/embed/9e8XbFFkDuA14402018-06-10T00:00:00+00:00yes https://riseof.ai/talks/building-european-ai-sovereignty-ronja-kemmer/https://i.ytimg.com/vi/okVNlMCnCrI/hqdefault.jpgBuilding European AI Sovereignty – Ronja Kemmer, Tina Klüwer, Mario Brandenburg (Rise of AI Conference 2026)At Rise of AI 2026 in Berlin, a panel on the Meta Stage discusses what European AI sovereignty means in practice. Moderator Mario Brandenburg opens by noting that Ronja Kemmer, originally announced from the Bundestag, called in sick and has been replaced by a representative from Nvidia's European public sector business. The other panelist is Tina Kluewer of AI Nation, a German government initiative bringing together regional AI startup support programs. The Nvidia representative frames sovereignty through a five-layer model (energy, chips, infrastructure, models, applications) and Nvidia's board-approved definition that sovereign AI is owned, operated and governed in-country. The panel debates how to measure sovereignty, its link to military security and quantum computing, why German AI startups struggle to scale despite a strong Mittelstand, whether GDPR and the coming AI Act help or hurt European competitiveness, and what Europe's context-rich manufacturing and healthcare data could contribute as a genuine advantage. The discussion closes with predictions about the panel topic in ten years.https://www.youtube.com/embed/okVNlMCnCrI28202026-07-15T00:00:00+00:00yes https://riseof.ai/talks/can-ai-ever-be-green-how-we-build-the-ai-factory-sustainably-christian/https://i.ytimg.com/vi/Zo5F6c9cvC8/hqdefault.jpgCan AI Ever Be Green? How We Build the AI Factory Sustainably – Christian Winterfeldt (Rise of AI Conference 2026)At Rise of AI 2026 in Berlin, Christian Winterfeldt of Dell Technologies, who leads Dell's data center business for Germany, Austria and Switzerland, argues that AI can become more sustainable through disciplined engineering rather than by avoiding the question. He opens with the scale of the problem: data centers will consume more than 2,000 terawatt-hours of energy by the end of the year, according to one study, roughly half of North America's total energy use and double the figure from three years ago. He explains that unlike CPU infrastructure, GPUs cannot be oversubscribed because their memory and bandwidth have hard limits, so the old cloud economics of 'more usage, lower cost' break down and orchestration replaces oversubscription. He presents the 'AI factory' as a full-stack production system optimized for useful output per watt, covering rack-scale design, liquid cooling, multi-tenant GPU scheduling, granular energy measurement, heat reuse, model-size choices and storage tiering. He describes a customer case where software optimization cut a GPU footprint from twelve GPUs to one, and closes with a five-step plan and the view that AI will remain a major energy consumer but can be built intelligently.https://www.youtube.com/embed/Zo5F6c9cvC816802026-07-15T00:00:00+00:00yes https://riseof.ai/talks/can-germany-be-a-technology-leader-in-ai-kai-zenner/https://i.ytimg.com/vi/coBrx6UCDHc/hqdefault.jpgCan Germany be a technology leader in AI? – Kai Zenner, Jörg Bienert, Jonas Andrulis, Amira Gutmann-Trieb (Rise of AI Conference 2023)At Rise of AI 2023 in Berlin, a panel with Kai Zenner, Jörg Bienert, Jonas Andrulis and Amira Gutmann-Trieb discusses whether Germany and Europe can lead in AI given the pending EU AI Act. Zenner, working on the AI Act negotiations for a European Parliament office, criticizes the Commission's original proposal as a horizontal framework applied too literally across sectors, and describes the Parliament's Article 8 fix giving high-risk obligations a sector-specific interpretation, and its unfinished attempt to close a loophole that let foundation-model providers like Google escape compliance while startups bore the burden, adding that much remains open. Andrulis, founder of Aleph Alpha, argues Europe's risk is hesitation, not technology, since his company already built multimodal and explainable language models but lacks the capital of US competitors like Microsoft-backed rivals. Bienert, president of KI Bundesverband, argues an early Council proposal treated general-purpose AI as automatically high-risk, calling this impractical, and describes a project building a shared European compute platform for research institutions and startups. The panel agrees Europe should build a 'trustworthy AI' brand but warns of repeating GDPR's slow, fragmented enforcement, and audience questions push back on whether 'European values' AI is actually a selling point abroad.https://www.youtube.com/embed/coBrx6UCDHc24602023-05-14T00:00:00+00:00yes https://riseof.ai/talks/can-we-hide-secrets-from-ai-shaun-moore/https://i.ytimg.com/vi/b2W06FEFOhg/hqdefault.jpgCan We Hide Secrets from AI? – Shaun Moore (Rise of AI Virtual Chat 2020)In a 2020 Rise of AI Virtual Chat, Fabian Westerheide interviews Shaun Moore, CEO of the computer vision company Trueface, about AI surveillance. Westerheide opens by surveying current uses, from France detecting mask compliance to Baidu's face and temperature scanning in China and Israeli border behavior analysis, and notes the EU's temporary ban on facial recognition alongside its own border control ambitions. Moore describes Trueface's shift from building cameras to selling algorithms and software that run entirely on client infrastructure, its use in touchless stadium access and age verification for alcohol and tobacco sales, and the company's 2017 partnership with the United Nations to build more globally representative training data after finding public datasets skewed heavily Caucasian and male. He argues facial recognition should stay a decision-support tool with a human always in the loop, describes Trueface's ethical screening of clients, and compares surveillance norms across the US, China and Europe. The conversation closes on data correlation as the deeper privacy issue, the three distinct uses of facial recognition, and AI's role in future warfare through infrastructure disruption rather than autonomous killing.https://www.youtube.com/embed/b2W06FEFOhg36602020-07-09T00:00:00+00:00yes https://riseof.ai/talks/can-you-get-past-your-meatbag-self-to-embrace-the-future-trent-mcconag/https://i.ytimg.com/vi/xvZUK06VAsI/hqdefault.jpgCan You Get Past Your Meatbag Self to Embrace the Future? – Trent McConaghy (Rise of AI Conference 2017)At Rise of AI 2017 in Berlin, Trent McConaghy argues that the biggest threat to humanity is not misaligned superintelligence but AI systems, no smarter than today's, gradually taking control of the world's capital resources in the name of efficiency. Drawing on his background in evolutionary AI and his current work on blockchain infrastructure, he describes how combining artificial general intelligence with decentralized autonomous organizations (DAOs) lets software agents own assets, earn income and reinvest it without any human able to switch them off. He illustrates this with an 'ArtDAO' that sells AI-generated art and compounds its earnings, and extends the logic to self-owning cars, trucks and power grids, comparing it to BMW and the semiconductor industry going 'fabless'. Rather than proposing regulation, environmental policy or universal basic income, which he says do not address this specific risk, McConaghy proposes that humans join the machines: build a shared interplanetary computational substrate and migrate human patterns of intelligence onto it, either through whole-brain uploading or, more plausibly in his view, through steadily increasing brain-computer-interface bandwidth, so humans become peers of AI rather than being optimized out of the system.https://www.youtube.com/embed/xvZUK06VAsI14402017-05-25T00:00:00+00:00yes https://riseof.ai/talks/challenges-of-the-european-ai-ecosystem-florian-sch-tz/https://i.ytimg.com/vi/IwgiP-Iv1Y4/hqdefault.jpgChallenges of the European AI Ecosystem – Florian Schütz, Vanessa Cann, Joanna Bryson, André Loesekrug-Pietri (Rise of AI Conference 2022)At Rise of AI 2022 in Berlin, a panel with Florian Schütz (K.I. Park), Joanna Bryson (Hertie School), André Loesekrug-Pietri (JEDI) and Vanessa Cann (German AI Association) discusses the state of the European AI ecosystem. Schütz opens by arguing that ecosystems are not needed to develop AI technology itself, but are essential to turn technology into real societal impact, since that requires values, regulation, funding, infrastructure, data, talent and users working together. Bryson presents patent and market-capitalisation data from a paper written with a colleague at DG Competition, arguing the EU and China are closer in AI patents and market capitalisation than commonly assumed, and that the US, not Europe, is the outlier. Loesekrug-Pietri describes building JEDI, a foundation modelled on DARPA, and criticises European fragmentation, weak deep-tech scale-up and dependency on foreign infrastructure, citing examples from space, chips and vaccines. Cann outlines Germany's strong AI research base and established companies, but points to weak corporate-startup collaboration, low research-to-product transfer, and underfunded startups as the main obstacles to scaling the ecosystem.https://www.youtube.com/embed/IwgiP-Iv1Y429402022-06-13T00:00:00+00:00yes https://riseof.ai/talks/challenges-of-the-german-ai-ecosystem-vanessa-cann/https://i.ytimg.com/vi/WuEbIpoa3-s/hqdefault.jpgChallenges of the German AI Ecosystem – Vanessa Cann (Rise of AI Summit 2020)At the Rise of AI Summit 2020, Vanessa Cann, Managing Director of the German AI Association (KI Bundesverband), presents findings from a study run with the German Startups Association, Telekom hubraum and the Institute for Applied Artificial Intelligence in Stuttgart. She argues Germany has strong preconditions, ranking second in AI research behind China and fourth in industrial GDP, but still fails to translate research into AI products, with only two German companies appearing on a widely used list of the top 100 global AI startups. She points to a large venture capital gap, a scarcity of AI startups compared with Israel, and weak connections between startups clustered in a few cities and the small and mid-sized companies that make up most of the economy. She proposes four steps toward AI leadership: clear and proportional regulation, more education on AI and entrepreneurship, direct state investment in young companies, and incentives for investors and established firms, then details her association's regulatory recommendations before taking audience questions on incentives, liability and why the well-known funding problem persists.https://www.youtube.com/embed/WuEbIpoa3-s16202020-11-20T00:00:00+00:00yes https://riseof.ai/talks/cognitive-claims-handling-with-ai-sofie-quidenus-wahlforss/https://i.ytimg.com/vi/astjnEdv96Y/hqdefault.jpgCognitive Claims Handling with AI – Sofie Quidenus-Wahlforss (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Sofie Quidenus-Wahlforss, CEO and founder of omni:us, describes her company's journey applying narrow AI to insurance claims handling and argues that general intelligence remains far off, so startups must focus on a specific, measurable use case. She traces her path from a document-scanning robot she built in 2004, which digitized over 980 million documents, through the realization that most digital documents like PDFs are not machine-readable, to founding omni:us and eventually narrowing its ambition from a broad, horizontal document-understanding platform serving 5-10 industries to a vertical focus on a single process: insurance claim handling. She explains that while standard approaches extract 7 to 14 data fields from a claim, omni:us technology extracts around 200, enabling a shift from process-driven to data-driven insurance. She describes the technical architecture of a reusable, scalable training engine combined with an industry-specific natural language processing layer, and closes by describing the cultural difficulty, for both her company and its insurance customers, of pushing large-scale transformation.https://www.youtube.com/embed/astjnEdv96Y14402019-07-15T00:00:00+00:00yes https://riseof.ai/talks/combining-privacy-and-ai-thomas-strottner/https://i.ytimg.com/vi/cZPSUdPpzTY/hqdefault.jpgCombining Privacy and AI – Thomas Strottner (Rise of AI Summit 2020)At the Rise of AI Summit 2020, Thomas Strottner, Head of Business Development at brighter AI Technologies, filling in for the company's CEO, explains how his company reconciles data privacy with AI development on camera data. He describes cameras as the richest sensor for AI use cases such as Amazon Go stores, smart city people counting and self-driving cars, and notes facial recognition systems can now track up to 20,000 key points on a face, which brings both useful applications and risks of abuse, citing facial recognition used to track Black Lives Matter protesters and for social scoring in authoritarian regimes. He surveys tightening regulation, including GDPR and California's new Consumer Privacy Act, and describes a perceived "AI privacy dilemma" between accurate models and privacy protection, which he argues is solvable through approaches like federated learning, privacy by default and privacy by design. He explains that pixelating faces and license plates degrades AI training data and introduces bias, and presents brighter AI's alternative: generating synthetic faces and license plates that preserve realism while, in tests against Microsoft Azure's facial recognition, reducing identity match to about 16%.https://www.youtube.com/embed/cZPSUdPpzTY12602020-11-20T00:00:00+00:00yes https://riseof.ai/talks/competing-with-giants-europe-s-way-forward-carla-hustedt/https://i.ytimg.com/vi/fxUvl6BTNxM/hqdefault.jpgCompeting with Giants: Europe’s Way Forward – Carla Hustedt, Kai Zenner, Aline Blankertz, Leonie Neuhäuser (Rise of AI Conference 2026)At Rise of AI 2026 in Berlin, a panel with Carla Hustedt (Mercator Foundation), Kai Zenner (European Parliament, adviser to MEP Axel Voss), Aline Blankertz (Rebalance Now) and Leonie Neuhaeuser (DeepL) discusses how Europe can compete with US and Chinese tech giants without copying them. Zenner describes the Brussels debate as split between a protectionist camp wanting to exclude non-European providers and a free-market camp opposed to any European preference, and presents a third "European way" that focuses on reducing excessive dependencies while accepting that Europe cannot lead in every area. Blankertz argues that democratic and regulatory sovereignty matter as much as company ownership, since some firms can afford to break existing laws, and calls for stronger competition-law enforcement against concentrated economic power. Neuhaeuser explains DeepL's move to a hybrid cloud strategy, combining its own European data centers with a new AWS partnership for latency and reliability reasons, and argues Europe's strength lies in tailored applications rather than a general-purpose frontier model. The panel also covers public procurement as a sovereignty tool, the Munich Linux migration, and the EU's AI Act omnibus simplification process.https://www.youtube.com/embed/fxUvl6BTNxM28202026-07-15T00:00:00+00:00yes https://riseof.ai/talks/create-an-ai-roadmap-for-business-christian-guttmann/https://i.ytimg.com/vi/kxiYWzbM6OA/hqdefault.jpgCreate an AI Roadmap for Business – Christian Guttmann (Rise of AI Virtual Chat 2020)In this Rise of AI Virtual Chat episode 17, recorded in September 2020, host Fabian Westerheide talks with Christian Guttmann, Chief AI Officer at TietoEVRY, founder of the Nordic AI Institute and professor of AI, about how companies build a realistic AI roadmap. Guttmann, who has a psychology background and a PhD in distributed multi-agent systems, reflects on a decade of AI hype and reality: funding and political attention have grown sharply, but adoption inside established companies remains slow outside fast movers like Google, Amazon and TikTok. He explains that not every AI approach needs large datasets, pointing to few-shot learning, deep reinforcement learning and knowledge graphs, and argues that common sense and causal reasoning, not just pattern matching, are the field's next real challenge. He then lays out a step-by-step roadmap: assess the company's identity and ambition, distinguish real autonomous AI from analytics or automation, start with meaningful iterative use cases, centralize standards and research while decentralizing customer work, and size internal AI teams to company scale. The conversation closes on automation versus augmentation, emotion AI and Guttmann's optimism about AI's role in healthcare and drug discovery over the next decade.https://www.youtube.com/embed/kxiYWzbM6OA37202020-09-10T00:00:00+00:00yes https://riseof.ai/talks/data-centric-ai-claudia-pohlink/https://i.ytimg.com/vi/_s6YP7zwcAI/hqdefault.jpgData Centric AI – Claudia Pohlink (Rise of AI Conference 2022)At Rise of AI 2022 in Berlin, Claudia Pohlink, chief expert for data at Deutsche Bahn, argues that AI progress is bottlenecked by data, not models. Inspired by Andrew Ng's push for 'data-centric AI', she contrasts research, where nearly 99 percent of papers focus on improving models and only about 1 percent on improving data, with practice, where up to 60-80 percent of effort in AI use cases goes into data preparation, sourcing and access negotiation. She cites a Gartner estimate that poor data quality costs organizations around 13 million dollars a year on average, and notes demand for data engineers now outpaces demand for data scientists. Pohlink describes Deutsche Bahn's Data Intelligence Center, built three years earlier around a House of Data, a House of AI and a House of 3C (community, change, communication), and the company's 2020 board resolution making data accessible company-wide by default unless explicitly restricted. She walks through the group's roadmap of a central data catalog, data governance roles and a planned move toward data mesh architecture, and closes by warning against skipping data work in favor of 'sexy' model-centric AI projects.https://www.youtube.com/embed/_s6YP7zwcAI16802022-06-13T00:00:00+00:00yes https://riseof.ai/talks/decentralized-ai-ben-goertzel/https://i.ytimg.com/vi/1QmsccY_EDM/hqdefault.jpgDecentralized AI – Ben Goertzel (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Ben Goertzel argues that a decentralized, self-organizing 'society and economy of minds' is the best route to both artificial general intelligence and a democratic, participatory global AI. He frames general intelligence as a spectrum on which humans sit far below possible superintelligence, and describes AI development moving from today's narrow-AI revolution toward an AGI revolution and eventually a superintelligence revolution. Goertzel warns that AI development is currently concentrated in a dozen corporations and two large governments, whose systems are mostly used for spying, killing, selling and betting, and that this narrow set of goals risks shaping the superintelligence that eventually emerges, while also magnifying global wealth inequality. His response is SingularityNET, a decentralized, blockchain-based AI platform he founded in 2017, funded via a token sale, where independent AI agents, including his own OpenCog architecture, can interoperate and offer services. He describes deployments including the Sophia robot, a pizza-delivery optimization project with Domino's, longevity research, and a new enterprise spin-off, Singularity Studio.https://www.youtube.com/embed/1QmsccY_EDM14402019-07-03T00:00:00+00:00yes https://riseof.ai/talks/deep-learning-to-save-lives-monishwaran-maheswaran/https://i.ytimg.com/vi/EqxtJyPI8rE/hqdefault.jpgDeep Learning to Save Lives – Monishwaran Maheswaran (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Monishwaran Maheswaran, a 12th-grade student who describes himself as a computer scientist, inventor and mathematician, presents two self-built deep learning projects aimed at healthcare. He traces his own path from teaching himself programming languages as a child to building an English-vocabulary app, an early chatbot, and, after encountering an accident involving a visually impaired person, a camera-and-earphone device that detects hazards such as crossroads and potholes and describes them in natural language. He argues deep learning's biggest impact will be in healthcare because of the volume of data the industry produces, and presents Project Health, a wristband that tracks tremor activity to detect Parkinson's disease years before symptoms appear, and Project Life, which analyzes smartphone behavioral data such as sleep, steps and web searches to detect emotional states linked to suicide risk. He states his own aim is to provide affordable, universal healthcare. A Q&A follows about funding, data sources and ethics approval for this kind of work.https://www.youtube.com/embed/EqxtJyPI8rE12602019-07-17T00:00:00+00:00yes https://riseof.ai/talks/deep-learning-future-of-ai-damian-borth/https://i.ytimg.com/vi/Kzj9P5BwFpQ/hqdefault.jpgDeep Learning: Future of AI – Damian Borth (Rise of AI Conference 2017)At Rise of AI 2017 in Berlin, Damian Borth, Director of the Deep Learning Competence Center at DFKI, traces how deep learning became the engine of the current AI wave. He opens with political context, from Angela Merkel's 2013 remark that the internet is uncharted territory to Barack Obama's 2016 comment that his successor would govern a society transformed by AI, and to AlphaGo's 2016 win over Lee Sedol. He explains why 2012 was the turning point for deep learning, when AlexNet won the ImageNet competition by a large margin thanks to three factors coming together: deeper networks, the large labeled ImageNet dataset, and GPU compute that Nvidia's Jensen Huang chose to support once researchers started repurposing graphics cards for training. Borth then covers post-2012 architectures, the privacy risks of models that memorize training data, his own team's pioneering work extracting sentiment from visual content, and the resulting Nvidia AI Lab recognition. He closes by arguing that society, not companies or politicians alone, must decide where AI's use should stop, and calls for risk-based classification and compliance systems for AI.https://www.youtube.com/embed/Kzj9P5BwFpQ15602017-05-25T00:00:00+00:00yes https://riseof.ai/talks/deep-tech-capabilities-in-intelligence-and-defense-myths-misery-and-mi/https://i.ytimg.com/vi/ZmlTMNzFghQ/hqdefault.jpgDeep tech capabilities in intelligence and defense: myths, misery and miracles – Sandro Gaycken (Rise of AI Conference 2023)At Rise of AI 2023 in Berlin, Sandro Gaycken, founder of Monarch, argues that despite popular myth, Western defense and intelligence agencies are not major drivers of deep-tech innovation. He frames the problem as three interlocking barriers he calls the 3P problem: payment, procurement and political procrastination. Public salaries cannot compete with industry pay for hackers, public procurement bodies such as Germany's BAAINBw take up to 18 months just to review a submission and require dozens of sign-offs, and politicians avoid deciding on technically complex, high-risk topics because failure is punished while inaction is not. As a result, he says, military AI is mostly bought from the consumer electronics and advertising industry rather than built for defense, which imports biases unsuited to battlefield conditions. He describes a Pentagon simulation in which two commercial AIs both recommended total nuclear annihilation, and warns that military AI systems are rarely built under vetted, secure conditions and are therefore highly hackable. He closes by describing intelligence use of AI as mainly dependent on the analyst asking the right questions.https://www.youtube.com/embed/ZmlTMNzFghQ15602023-05-14T00:00:00+00:00yes https://riseof.ai/talks/digital-ethics-shaping-value-based-ai-manuela-mackert/https://i.ytimg.com/vi/SVI-ROBzJ4w/hqdefault.jpgDigital Ethics: Shaping Value-Based AI – Manuela Mackert (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Manuela Mackert, Chief Compliance Officer at Deutsche Telekom AG, argues that digital ethics is as important as the technology itself and that value-based AI is a competitive advantage, not a brake on innovation. She insists that values such as freedom, self-determination, transparency, respect, tolerance and appreciation must hold in the digital world exactly as they do in the analog one, and that humans must stay in the loop so AI never becomes uncontrolled. She describes how Deutsche Telekom turned these principles into practice: AI guideline development built on dialogue with partners in the US, Israel, academia, NGOs and companies; a crowdsourced, cross-national ethics team; mandatory review of AI-related projects through an internal privacy and security governance process; and a dedicated ethics center in Berlin that makes AI applications, such as a dementia-therapy robot, tangible for customers. She calls for European sandboxes to test AI safely, a European data marketplace, and closer cooperation with the US and China, while warning that future risks, including manipulation of brain implants, require clear guardrails and certification, especially in healthcare.https://www.youtube.com/embed/SVI-ROBzJ4w10802019-07-03T00:00:00+00:00yes https://riseof.ai/talks/embodied-ai-how-will-it-define-our-future-elisa-czerski/https://i.ytimg.com/vi/DHNQ6jD-t3w/hqdefault.jpgEmbodied AI: How will it define our future? – Elisa Czerski (Rise of AI Conference 2023)At Rise of AI 2023 in Berlin, Elisa Czerski, founder and CEO of N Robotics, argues embodied AI, artificial intelligence integrated into a physical system like a robot, will matter more than software-only AI because it interacts directly with the world and forces developers to confront the alignment problem earlier, since a robot's behavior can be tested in the real environment rather than judged purely on model outputs. She traces the term to combining 'robot', a machine that performs work, with AI, and argues embodied systems raise distinct risks around safety, privacy and autonomous data collection that receive less regulatory attention than software AI, including questions about autonomous weapons. N Robotics builds mobile robots end-to-end, from hardware to software, for use cases like construction and energy data collection, and is launching a fully open-source bipedal robot. Czerski argues true humanoid robots are not the right shape mechanically, and that autonomy and fast production scaling, not appearance, will determine which robotics companies succeed. She describes funding as harder for a female, first-time, deep-tech founder in Germany, and, together with audience members, debates whether Asia or Europe will lead the next wave of robotics.https://www.youtube.com/embed/DHNQ6jD-t3w16202023-05-14T00:00:00+00:00yes https://riseof.ai/talks/enterprise-ai-using-ai-to-create-business-value-feiyu-xu/https://i.ytimg.com/vi/5-7JPSi5Tew/hqdefault.jpgEnterprise AI: Using AI to Create Business Value – Feiyu Xu (Rise of AI Conference 2022)At Rise of AI 2022 in Berlin, Dr. Feiyu Xu, Senior Vice President and Global Head of Artificial Intelligence at SAP, argues that after decades of progress, from machine translation once taking minutes per sentence to now running in milliseconds, AI should be used to remove boring, repetitive work from corporate life the way it already removes friction from consumer life. She presents three pillars of SAP's enterprise AI strategy: intelligent applications customers can use out of the box with no configuration, adaptability so customers can extend applications to their own industry needs, and trustworthy, responsible AI given that SAP's applications run mission-critical processes in HR, finance and supply chain. She walks through four end-to-end business processes SAP targets with AI, lead to cash, design to operate, source to pay and recruit to retire, and gives concrete results, including a supply chain forecast that dropped from 160 hours to 4 and now considers 66 million data points instead of 22,000, and a Concur travel-expense product used by 26,000 customers that now auto-audits 70% of expense reports. She closes by describing SAP's AI ethics governance, built since 2018 around guiding principles, an internal steering committee and an external expert panel.https://www.youtube.com/embed/5-7JPSi5Tew23402022-06-13T00:00:00+00:00yes https://riseof.ai/talks/esa-ai-demo-how-to-apply-ai-on-earth-data-esa/https://i.ytimg.com/vi/zrJgY4r4PRI/hqdefault.jpgESA AI Demo: How to Apply AI on Earth Data – ESA, LiveEO, Birds.ai (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, a representative of the European Space Agency introduces ESA's free Copernicus Earth-observation data before two startups demo how they apply AI to it. The ESA speaker explains that the Sentinel satellite constellation delivers petabytes of optical, radar and atmospheric data at 10-meter resolution roughly twice a week, free and guaranteed for decades, and describes ESA's challenge programs and plans to run AI directly on satellites. Daniel Seidel, founder and CTO of LiveEO, then shows how his company combines satellite imagery with AI to monitor infrastructure like electricity grids and railway vegetation, using Deutsche Bahn as its founding case before expanding to US and Austrian grids. Anouk Visser, co-founder and CTO of Birds.ai, closes by demonstrating how her company uses drone RGB and thermal imagery with supervised machine learning to detect defects on solar farms and wind turbines, delivered through a subscription platform called Bird's Eye View. A Q&A covers workflow ownership and each startup's path from an earlier, different idea to its current business.https://www.youtube.com/embed/zrJgY4r4PRI30002019-07-19T00:00:00+00:00yes https://riseof.ai/talks/ethics-of-algorithms-from-theoretical-discussion-to-practical-applicat/https://i.ytimg.com/vi/xlH4RlVD8Ko/hqdefault.jpgEthics of Algorithms: From Theoretical Discussion to Practical Application (Rise of AI Summit 2020)At the Rise of AI Summit 2020 in Berlin, a panel hosted by KI Park Germany discusses how to move ethical principles for AI from theory into practice. The panel brings together Carla Hustedt, head of the Ethics of Algorithms project at Bertelsmann Stiftung, a member of Volkswagen's group board of management responsible for integrity and legal affairs, the co-founder of a privacy-focused data science company, and philosopher Marcus Gabriel of the University of Bonn, moderated by an AI consultant named Peter. Gabriel defines ethics as the discipline studying moral facts, and argues that 'strong AI' in John Searle's sense will never exist, so the real ethical stakes lie in 'weak AI' systems like news feed ranking or predictive policing. Hustedt argues that bias in algorithmic systems usually originates in human decisions about goals, data and implementation, not the technology alone, and describes the algo.rules framework her organization developed as a set of process standards rather than new fundamental rights. The panel also debates predictive policing, responsibility for trustworthy AI, and whether European ethics framing is a genuine competitive advantage over the US and China.https://www.youtube.com/embed/xlH4RlVD8Ko18602020-11-20T00:00:00+00:00yes https://riseof.ai/talks/europe-s-ai-dilemma-catching-up-or-leading-the-way-kai-zenner/https://i.ytimg.com/vi/xiaaJl7NAFw/hqdefault.jpgEurope’s AI Dilemma: Catching Up or Leading the Way? – Kai Zenner, Martina Silov, Anna Christmann, Stefanie Söhnchen (Rise of AI Conference 2024)At Rise of AI 2024, a panel moderated by Stefanie Soehnchen (PIABO Communications) with Anna Christmann (German Bundestag, federal coordinator for aerospace and commissioner for startups and the digital economy), Martina Silov (president of CroAI) and Kai Zenner (policy adviser, European Parliament) discusses whether Europe is leading or falling behind in AI. All three agree Europe is neither leading nor left behind: the AI Act laid regulatory groundwork, but attention must now shift to applying AI across sectors, with more investment, open data and talent. Christmann calls for a 'European Tech Deal' alongside the Green Deal. Silov argues Europe has the scientific talent but lacks business, marketing and management culture, and a tolerance for startup failure, pointing to Croatia's own unicorns built despite a small market. Zenner says Brussels still works in policy silos, that the AI Act's European ethical principles are 'hidden' in the text rather than stated upfront, and cites the underfunded AI Lighthouse initiative as an example of good ideas failing on investment and national rivalry over its location. The panel closes on the need for larger, braver private and public investment and stronger cross-border European hubs.https://www.youtube.com/embed/xiaaJl7NAFw25202024-05-20T00:00:00+00:00yes https://riseof.ai/talks/europe-s-ai-liftoff-antonio-kr-ger/https://i.ytimg.com/vi/8gwttDnGExs/hqdefault.jpgEurope’s AI Liftoff – Antonio Krüger (Rise of AI Conference 2026)At Rise of AI 2026 in Berlin, Antonio Krüger, CEO of DFKI, argues that Europe is now in a genuine "liftoff" phase for AI rather than merely trying to catch up with the US and China. He says Europe cannot compete on the scale of US and Chinese frontier-model spending, so its opportunity lies in a different niche: human- and society-oriented AI, backed by strong research and education, growing numbers of graduate and PhD students, and industrial data that US and Chinese models, built mainly on consumer data, largely lack. He points to fresh capital flowing into European infrastructure, including a planned Microsoft investment of around 50 billion US dollars and new research centers in Barcelona and Berlin, plus AI factories under development in Germany. Krüger stresses that DFKI's own focus is trustworthy AI, building systems that can be relied on in the physical world and that learn from failure, and he calls for closer European collaboration, since no single country or stakeholder group can drive AI sovereignty alone.https://www.youtube.com/embed/8gwttDnGExs18002026-07-15T00:00:00+00:00yes https://riseof.ai/talks/exciting-entities-from-the-future-ronnie-vuine/https://i.ytimg.com/vi/T1gkqR3edeo/hqdefault.jpgExciting Entities from the Future – Ronnie Vuine (Rise of AI Conference 2017)At Rise of AI 2017 in Berlin, Ronnie Vuine argues that today's AI does not yet exist as popularly imagined and is, in his words, a fantasy, and explores why that fantasy is nonetheless what makes AI exciting. He says the field has gotten very good at pattern recognition and, in his own company's work, at reinforcement learning that links pattern recognition to acting systems, but that no one has any idea how to build the actual thinking that would take context, culture and long-term deliberation into account, and that this gap cannot be closed by scaling neural networks with more data. He traces this excitement to science fiction, telling the story of 1920s writer and rocket pioneer Max Valier, whose fictional hero anticipates the atomic bomb and who later dies testing real rocket engines, a lineage he connects to Wernher von Braun and the postwar American space program. He then reads a passage from William Gibson's Neuromancer to show how literature intensifies technological fantasies, arguing Gibson did not predict the future but helped create it, and closes with a quote from Mark Fisher on fiction and reality merging.https://www.youtube.com/embed/T1gkqR3edeo10202017-05-25T00:00:00+00:00yes https://riseof.ai/talks/exponential-society-2030-martin-spindler/https://i.ytimg.com/vi/QfiAvzc9b2U/hqdefault.jpgExponential Society 2030 – Martin Spindler (Rise of AI Conference 2017)At Rise of AI 2017 in Berlin, Martin Spindler, describing himself as a historian rather than a futurist, argues that looking at past visions of the future is the best way to calibrate forecasts about AI and 2030. He opens with a 1970 artwork imagining a global information network and early computers used for intercontinental missile calculations, to show that people overestimate technology's short-term impact and underestimate its long-term impact. He traces Moore's Law and notes computing power grew by roughly a billion times between the 1956 Dartmouth conference, where the term artificial intelligence was coined, and today. He tests the claim that AI will transform the world like electricity did by revisiting electrification's history of platform battles, military applications and today's collapsing coal stock values, then lays out four scenarios for 2030: a runaway technological singularity, sigmoid-curve disruption as seen in self-driving cars and media, data-driven centralization, and a volatile 'world of asymmetries' created by cheap, widely accessible AI, illustrated with consumer drones used as weapons.https://www.youtube.com/embed/QfiAvzc9b2U15002017-05-25T00:00:00+00:00yes https://riseof.ai/talks/face-recognition-shaun-moore/https://i.ytimg.com/vi/4lvUBucQkLw/hqdefault.jpgFace Recognition – Shaun Moore (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Shaun Moore, CEO of Trueface, argues that facial recognition is becoming a mainstream, real-time technology as camera infrastructure scales and processing shrinks from hundreds of megabytes to a few megabytes that can run at the edge on devices like a Raspberry Pi. He traces the technology from hand-drawn proportion analysis in 1960 through the failed 2002 Super Bowl trial, Facebook's 2010 auto-tagging research, and Google's 2015 false claim of 100 percent accuracy, which was undermined by its gorilla-tagging error. Moore describes applications in travel, school safety, fraud reduction, access control and convenience, while emphasizing that public training datasets are skewed 70-80 percent white male, producing biased algorithms unless companies source balanced or synthetic data, including data generated with generative adversarial networks. He distinguishes anonymous, template-based recognition from data storage that identifies individuals, and calls for federal or international regulation, arguing that responsible use, not banning the technology, is the right path forward.https://www.youtube.com/embed/4lvUBucQkLw18602019-09-04T00:00:00+00:00yes https://riseof.ai/talks/facebook-s-perspectives-on-an-ethical-and-privacy-by-design-approach-t/https://i.ytimg.com/vi/OGHJi6bJFEQ/hqdefault.jpgFacebook’s Perspectives on an Ethical and Privacy by Design Approach to AI – Norberto Andrade (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Norberto Andrade, Privacy and Public Policy Manager at Facebook, presents three perspectives on how Facebook builds AI: design, product and research. He introduces Facebook's design team's "four quadrants" framework, which plots products from small-scale pixels to full ecosystems, and from individual users to global society, arguing ethical risk grows as products scale up in both dimensions. He describes AI as foundational to Facebook, powering newsfeed ranking and translating over 6 billion posts a day, and previews the Codec Avatars project, which uses machine learning to animate ultra-realistic avatars for remote interaction in AR/VR, while flagging open questions on diverse training data and avatar authentication. He explains that AI removes 99.6 percent of fake accounts before users report them, and outlines Facebook's fairness process across people, data and algorithms, including subgroup calibration and documented decision thresholds. He closes describing the Facebook AI Research lab's open-research mission and Facebook's support for an AI ethics institute at the Technical University of Munich.https://www.youtube.com/embed/OGHJi6bJFEQ14402019-07-01T00:00:00+00:00yes https://riseof.ai/talks/from-industrial-powerhouse-to-ai-powerhouse-thomas-jarzombek/https://i.ytimg.com/vi/5TcxdoQd5ks/hqdefault.jpgFrom Industrial Powerhouse to AI Powerhouse – Thomas Jarzombek (Rise of AI Conference 2026)At Rise of AI 2026 in Berlin, Thomas Jarzombek, Parliamentary State Secretary at Germany's digitalization ministry, reviews his first year in office and argues Germany should turn its industrial strength into AI competitiveness. He describes ongoing EU trilogue negotiations to simplify the AI Act, including extending high-risk-system deadlines by a year and working to exempt the Machinery Directive from the Act's scope, alongside a national German AI Act and a planned one-stop-shop regulatory model. He presents three government AI projects: Spark, an open-source tool that checks infrastructure-project paperwork in hours instead of about half a year and can cut approval time in half; the Agentic AI Hub, which pairs startups with municipalities to modernize legacy government software; and the Deutschland Stack, a sovereign compute platform built on European cloud providers. He argues against building an independent European alternative to US large language models, favoring what he calls blended sovereignty, integrating strong German startups into global AI supply chains instead. In Q&A he discusses SME adoption, shadow AI use by public servants, and the upcoming EU Digital Identity Wallet.https://www.youtube.com/embed/5TcxdoQd5ks14402026-07-15T00:00:00+00:00yes https://riseof.ai/talks/from-single-ai-to-multi-ai-systems-christian-guttmann/https://i.ytimg.com/vi/mr6ySQj5PIE/hqdefault.jpgFrom Single AI to Multi AI Systems – Christian Guttmann (Rise of AI Conference 2025)At Rise of AI 2025 in Berlin, Christian Guttmann, Executive Director of the Nordic AI Institute, argues that large language models are a narrow slice of AI and that the deeper, decades-old field of multi-agent systems deserves more attention as agent deployment accelerates. Drawing on his PhD work on the RoboCup grand challenge, which aims for autonomous humanoid robots to beat the reigning human soccer World Cup champions by 2050, he explains why multi-agent problems differ from static games like chess or Go. He walks through applications he has built, including BDI adherence agents for chronic disease care in Australia, traffic-light coordination researched by Anna Bazzan that Google later showed cut New York traffic by 30 percent and pollution by 10 percent, and micro-simulations of the Swedish population used to model pandemics twenty years before COVID-19. He defines multi-agent systems through cooperating or competing agents with private world models, collaborative planning and game theory such as Nash equilibrium, then lists dos and don'ts for enterprise deployment, warning that naive LLM-wrapped agents and unnecessary autonomy for homogeneous systems are common failure modes. He closes on quantum computing's potential for multi-agent reinforcement learning, followed by a Q&A on investment timing.https://www.youtube.com/embed/mr6ySQj5PIE18002025-05-21T00:00:00+00:00yes https://riseof.ai/talks/from-statistics-to-ml-to-ai-steffen-wachenfeld/https://i.ytimg.com/vi/_bGCDCXvvXc/hqdefault.jpgFrom Statistics to ML to AI – Steffen Wachenfeld (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, Steffen Wachenfeld, Chief Product Officer at WeQ, argues that companies should not skip stages when introducing intelligent systems, moving instead from simple statistics to machine learning and only then to what he considers true AI. Drawing on his experience in performance marketing, he walks through the economics of buying ad impressions and explains how a company first improves results with basic counting and A/B testing, which only optimizes one variable at a time, before moving to machine learning that handles many variables at once, powering recommenders and real-time programmatic ad auctions decided within 50 to 200 milliseconds. He calls that stage engineering and machine learning, not AI. He defines AI as a system whose behavior becomes human-like: it observes, learns patterns and then acts on its own, such as detecting fraudulent ad traffic and notifying an account manager without being asked. He closes by saying the useful cases are ones like answering complex analytical questions that would otherwise take a person half an hour, not chatbots that just answer simple FAQs.https://www.youtube.com/embed/_bGCDCXvvXc13202018-06-10T00:00:00+00:00yes https://riseof.ai/talks/future-optimism-ai-a-new-system-chris-boos/https://i.ytimg.com/vi/S5lskRm4i6E/hqdefault.jpgFuture Optimism: AI = A New System? – Chris Boos (Rise of AI Virtual Chat 2020)At a Rise of AI Virtual Chat in 2020, host Fabian Westerheide interviews Chris Boos, founder of Arago and member of Germany's digital council, about what he calls future optimism: the idea that AI-driven change is bringing about a new economic system. Boos argues the transition is evolution rather than revolution, and that industrialization is ending because machines now execute efficiently regardless of human process design, pushing society toward a knowledge or experience economy. He discusses why companies struggle to apply AI even when they know they should, arguing that unlike consumers, organizations need every internal stakeholder pulling in the same direction, and that the coronavirus crisis has forced overdue change management. He describes his own experience advising the German government and helping build a privacy-preserving corona contact-tracing backend, and argues Europe should focus on digitizing its established industries rather than trying to copy Silicon Valley or China. He closes by arguing AI is a neutral tool that amplifies human bias unless people also learn to combine rational thinking with emotion.https://www.youtube.com/embed/S5lskRm4i6E37802020-06-15T00:00:00+00:00yes https://riseof.ai/talks/gdpr-ai-the-twain-shall-meet-labhesh-patel/https://i.ytimg.com/vi/ke2WZ9YXYno/hqdefault.jpgGDPR & AI: The Twain Shall Meet – Labhesh Patel (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, Labhesh Patel, CTO and chief scientist at Jumio, explains how the EU's General Data Protection Regulation, taking effect a week after the talk, will reshape machine learning workflows. He describes Jumio's business verifying identities online by comparing a selfie to an ID document using machine learning and human review, which puts the company squarely under GDPR because it handles images, names, addresses and birth dates. He outlines the regulation's two fine tiers, up to 20 million euros or 4% of global revenue, and explains that GDPR now makes data processors, not just controllers, liable for breaches. Patel lays out practical steps toward compliance: encryption, human review of automated decisions under GDPR's right to explanation, configurable data retention, and 72-hour breach notification. He introduces 'compliant machine learning', building privacy and security into every stage of a pipeline, from data acquisition and tagging to training, deployment and evaluation, and explains why data from different customers cannot be commingled to train one shared model under the regulation's data minimization principle.https://www.youtube.com/embed/ke2WZ9YXYno10802018-06-10T00:00:00+00:00yes https://riseof.ai/talks/genai-driven-workflow-optimization-from-concept-to-execution-oliver-if/https://i.ytimg.com/vi/BES23PMGff4/hqdefault.jpgGenAI Driven Workflow Optimization: From Concept to Execution – Oliver Iff (Rise of AI Conference 2024)At Rise of AI 2024 in Berlin, Oliver Iff, data scientist at SVA System Vertrieb Alexander GmbH, presents a technical walkthrough of a generative-AI system his team built for clients to retrieve process knowledge scattered across an organization. He describes a multi-agent architecture in which large language models translate a client query, for example about a production facility, into a chain of function calls against data sources such as SQL, vector databases or the Signavio process-management tool, with each agent specialized for a narrow domain rather than relying on one large general-purpose model. The system runs on IBM's watsonx.ai platform, letting the team swap foundation models, including IBM's Granite series, and access them via REST API, while watsonx.governance tracks model lineage, fairness and bias metrics for EU AI Act compliance. He details the pipeline: converting Signavio process data via BPMN and JSON into embeddings stored in Elasticsearch, retrieving processes through a process agent using Granite, and generating dashboards and Python code through a code-generation agent using StarCoder. He closes citing productivity gains of up to 80 percent in comparable use cases such as HR or customer support.https://www.youtube.com/embed/BES23PMGff412002024-05-21T00:00:00+00:00yes https://riseof.ai/talks/generative-ai-for-industries-feiyu-xu/https://i.ytimg.com/vi/4i8chZ9oT8E/hqdefault.jpgGenerative AI for Industries – Feiyu Xu (Rise of AI Conference 2023)At Rise of AI 2023 in Berlin, Feiyu Xu, Senior VP and Global Head of AI at SAP, presents SAP's view of generative AI for enterprise and industry. The talk opens with remarks from Thomas, an SAP board member, who says SAP identified more than 80 generative AI use cases within a few weeks, warns that almost three quarters of AI models come from the US and 15 percent from China, and argues Europe must not miss this shift, pointing to SAP's role in the LEAM initiative for large European AI models. Xu then explains SAP's two-pillar strategy of embedding AI into business applications and enabling low-touch, no-touch innovation across four core business processes, describes advantages of generative over narrow AI such as reduced annotation needs, and outlines a three-step adoption path for companies: use existing models as-is, fine-tune on proprietary data, or invest in further research for data types like tabular, time-series, chemical and biological data. She closes on SAP's AI ethics governance, including a monthly cross-functional steering committee.https://www.youtube.com/embed/4i8chZ9oT8E19802023-05-14T00:00:00+00:00yes https://riseof.ai/talks/germany-s-strategy-for-ai-dorothee-b-r/https://i.ytimg.com/vi/ue1zbd1YYO8/hqdefault.jpgGermany’s Strategy for AI – Dorothee Bär (Rise of AI Summit 2020)At the Rise of AI Summit 2020, Dorothee Bär, Germany's Minister of State to the Federal Chancellor and Government Commissioner for Digital Affairs, presents Germany's AI strategy and its planned next steps. She frames the goal as an "AI-empowered society" built on European values and technological sovereignty, arguing Germany should set its own course rather than only reacting to the US and China. She reports the federal government increased its AI funding commitment from 3 billion to 5 billion euros by 2025, with the additional 2 billion earmarked for state-of-the-art computing infrastructure, and names three priority fields of action: upgrading AI infrastructure and computing power, strengthening and better internationally showcasing German AI research, and lowering financial, cultural and staffing hurdles for SMEs through funding instruments, regional networking and regulatory sandboxes. In the following Q&A, she argues European AI, built on stronger data-protection and ethics standards, has a long-term competitive advantage over China, and that the COVID-19 crisis made the case for digitization and AI investment easier to make within government, not harder.https://www.youtube.com/embed/ue1zbd1YYO815002020-11-20T00:00:00+00:00yes https://riseof.ai/talks/global-ai-echoes-bj-rn-bringmann/https://i.ytimg.com/vi/6qEIP_N1sBY/hqdefault.jpgGlobal AI Echoes – Björn Bringmann (Rise of AI Conference 2024)At Rise of AI 2024 in Berlin, Björn Bringmann, Managing Director and Lead at the AI Institute of Deloitte Germany, presents findings from Deloitte's quarterly AI surveys alongside outside data such as the Stanford AI Index. He argues that ChatGPT made AI tangible almost overnight despite remaining one of the most opaque models ever released, and reviews recent milestones including AlphaFold 3, open-source models like Llama reaching top-tier leaderboard scores, the EU AI Act, new Nvidia chips, and European generative AI players such as Mistral and Aleph Alpha. Using an AI ranking that scores countries on implementation, innovation and investment, he shows Germany performing reasonably on government strategy and operational metrics but slipping in research and commercialization, and highlights a large gap in R&D spending between the top US, Chinese and German companies. He walks through Deloitte survey data on German and global sentiment: perceived threat from generative AI to business models, high productivity expectations, shifting adoption priorities, talent and governance barriers, uneven employee access to GenAI tools, and views on whether AI will centralize or decentralize power. He closes urging German and European companies to move faster and pursue more ambitious "moonshot" projects.https://www.youtube.com/embed/6qEIP_N1sBY15002024-05-20T00:00:00+00:00yes https://riseof.ai/talks/globally-sourced-data-for-ai-training-the-how-to-of-ethical-and-compli/https://i.ytimg.com/vi/nRGO4gSsHb0/hqdefault.jpgGlobally Sourced Data for AI Training: The How-To of Ethical and Compliant Collection – Marian Gläser (Rise of AI Conference 2023)At Rise of AI 2023 in Berlin, Marian Gläser, co-founder and CEO of brighter AI, argues that data privacy regulation is a permanent, worldwide feature of AI development rather than a temporary obstacle. He traces privacy's legal history from a 1361 anti-stalking law and 1888 camera-driven concerns through the UN's 1948 recognition of privacy as a fundamental right to the 2018 GDPR and today's landscape, where Gartner predicts 75% of the world's population will be covered by some data privacy regulation. Using the example of a tier-one automotive company collecting camera data in Europe, labeling it in Brazil, training models in the US and validating them in Japan, he shows how GDPR, Brazil's LGPD, US state laws and Japanese norms each impose different, non-consent-based compliance burdens on the same data pipeline. He describes brighter AI's own anonymization work, including replacing faces and license plates with artificial ones for a public Valeo dataset, and argues that companies like his let clients forget about regulation by handling privacy continuously, so that innovation and privacy can be pursued together rather than traded off against each other.https://www.youtube.com/embed/nRGO4gSsHb017402023-05-14T00:00:00+00:00yes https://riseof.ai/talks/good-news-from-europe-larissa-holzki/https://i.ytimg.com/vi/gz8GqHXhBfA/hqdefault.jpgGood News from Europe – Larissa Holzki, Peter Sarlin, Jonas Andrulis (Rise of AI Conference 2025)At the opening panel of Rise of AI 2025 in Berlin, moderator Larissa Holzki, Chief Correspondent Tech at Handelsblatt, asks Peter Sarlin, CEO of Silo AI, and Jonas Andrulis, founder and CEO of Aleph Alpha, to find good news for Europe against a week of headlines dominated by the US Stargate infrastructure project, China's DeepSeek model, and multi-billion-dollar funding rounds for OpenAI, Anthropic and xAI. Andrulis argues infrastructure spending is a distraction unless it follows genuine value creation, while Sarlin says Europe's path runs through products, not the biggest data centers, pointing to a fragmented single market as the real barrier to scale. The panel covers Aleph Alpha's tokenizer-free transformer architecture, developed with Silo AI, claimed to give large efficiency and fine-tuning gains for low-resource languages; Silo AI's $665 million sale to AMD, framed by Sarlin as a European success rather than a loss; and Andrulis's account of public criticism after Aleph Alpha avoided the race for general-purpose frontier models. Both argue Europe should put AI at the core of transforming industries like biopharma, automotive and manufacturing rather than chasing efficiency gains alone, and call for stronger, more concentrated European AI ecosystems and a genuine single market.https://www.youtube.com/embed/gz8GqHXhBfA28202025-05-21T00:00:00+00:00yes https://riseof.ai/talks/good-news-from-germany-ai-panel-discussion-carsten-kraus/https://i.ytimg.com/vi/HpqM6gtqrpc/hqdefault.jpgGood News from Germany? AI Panel Discussion – Carsten Kraus, Markus Hacker, Stefanie Söhnchen, Vanessa Cann (Rise of AI Conference 2025)At Rise of AI 2025 in Berlin, a panel moderated by Stefanie Söhnchen of PIABO Communications, with Vanessa Cann (managing director for data and AI at Accenture and managing director of the German AI Association), Markus Hacker (senior regional director enterprise business DACH at Nvidia) and Carsten Kraus (founder and CEO of Casablanca AI), discusses whether Germany can overcome its reputation for AI pessimism. The panelists argue against constant comparison with the US and China, with Kraus urging Germany to move past a cultural 'angst' that slows adoption of imperfect but working technology, and Hacker urging a focus on domestic strengths such as DeepL, Black Forest Labs and Nvidia's digital-twin work with Sparkassen Finanzinformatik and KION. Cann reports that international investors increasingly see Europe as regulating rather than innovating, citing the EU AI Act's reputation, but also cites growth of the German AI Association (KI Bundesverband) to over 500 members and a shift among startups toward vertical SaaS. The panel identifies a persistent gap between academic research and commercialization, a lack of incentives for bold risk-taking inside companies and universities, and a cultural discomfort with visible success, and calls for more academia-industry connections modeled on Munich's UnternehmerTUM.https://www.youtube.com/embed/HpqM6gtqrpc32402025-05-21T00:00:00+00:00yes https://riseof.ai/talks/hacking-ai-data-poisoning-and-the-cybersecurity-challenge-mirko-ross/https://i.ytimg.com/vi/FJTGDtVsIEw/hqdefault.jpgHacking AI: Data Poisoning and the Cybersecurity Challenge – Mirko Ross (Rise of AI Conference 2023)At Rise of AI 2023, Mirko Ross, CEO of asvin, argues that the AI industry is repeating the security mistakes the web industry made around 1997-98, when developers trusted any data entered into online forms until SQL injection attacks taught them otherwise. He says AI systems face an equivalent lesson with data poisoning: attackers who manipulate training data or exploit a model's neural-network structure can force a chosen, non-random output, for example making an autonomous vehicle ignore a stop sign. Drawing on research asvin began about four or five years before this talk, well before ChatGPT-driven public debate, he traces the evolution of adversarial attacks from early 2015-era image-recognition exploits, through backdoor attacks planted during retraining of public models, to 2022-era work fooling 3D object recognition from any viewing angle. He demonstrates a practical defense, reducing image bit-depth or smoothing to strip out adversarial disturbance patterns while preserving accuracy, and closes by discussing prompt-based jailbreaks of ChatGPT's content filters and the need for a responsible-disclosure culture modeled on the software industry's, plus scrutiny of AI supply chains such as outsourced data labeling.https://www.youtube.com/embed/FJTGDtVsIEw21602023-05-14T00:00:00+00:00yes https://riseof.ai/talks/how-ai-adaptive-technology-can-upgrade-education-kp-thai/https://i.ytimg.com/vi/m5qvIMthbTc/hqdefault.jpgHow AI Adaptive Technology Can Upgrade Education – KP Thai (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, KP Thai, senior learning and data scientist at Squirrel AI Learning, argues that AI can redefine education rather than just make it more efficient. Using the SAMR model, he distinguishes substitution and augmentation, which merely enhance existing teaching, from modification and redefinition, where AI changes the paradigm itself by moving students from passive to active learning and shifting teachers from the 'sage on the stage' to a coaching role supported by an AI 'assistant coach'. He describes Squirrel AI's after-school, business-to-consumer model in China, built on granular knowledge components, a probabilistic model of what each student knows, and a virtual personal assistant that uses natural language dialogue to diagnose misconceptions behind wrong answers. He reports that external randomized controlled trials across more than 18 studies show students using Squirrel AI outperform peers in traditional instruction, including some taught at favorable teacher-to-student ratios, learning the same content faster. Founded in 2014, the company operates over 1,700 learning centers in 200 Chinese cities and is expanding internationally through research partnerships.https://www.youtube.com/embed/m5qvIMthbTc19802019-07-15T00:00:00+00:00yes https://riseof.ai/talks/how-ai-and-deep-learning-could-affect-climate-change-florin-manaila/https://i.ytimg.com/vi/o9HjkBIDkjY/hqdefault.jpgHow AI and Deep Learning Could Affect Climate Change – Florin Manaila (Rise of AI Summit 2020)At Rise of AI Summit 2020, Florin Manaila, Senior AI Architect and Inventor at IBM Systems Hardware Europe, addresses the carbon footprint of training AI systems on the Applied AI Day/Future Space track. Speech recognition for this recording failed, so no transcript is available, and this page is built from the YouTube description alone. According to that description, data scientists commonly train AI systems on huge quantities of data with almost no consideration of the resulting CO2 impact. Manaila's stated aim is to give data scientists visibility into the carbon footprint of their training choices and to explore how CO2 limits could be enforced at the AI data center level. No further detail, such as specific numbers, tools, or case studies discussed in the talk, could be confirmed from the available material, since the auto-generated transcript could not be recovered. Readers wanting the concrete methods or figures Manaila presented should watch the original 29-minute recording directly.https://www.youtube.com/embed/o9HjkBIDkjY17402020-11-30T00:00:00+00:00yes https://riseof.ai/talks/how-bias-impacts-ai-shaun-moore/https://i.ytimg.com/vi/bf7NVF8xmOg/hqdefault.jpgHow Bias Impacts AI – Shaun Moore (Rise of AI Conference 2023)At Rise of AI 2023 in Berlin, Shaun Moore, Chief AI Officer at Pangiam and former founder of facial recognition company TrueFace, which Pangiam acquired in 2021, argues that facial recognition can be deployed responsibly only if "humanity first" guides every stage of development and deployment. He traces the technology's history from Woodrow Wilson Bledsoe's 1960s hand-geometry comparisons through the first correct computer match in 1991, its 2001 Super Bowl use on 60,000 to 70,000 people, Facebook's 2010 mass-market photo tagging, and the 2017 iPhone X, and notes there are now about 1 billion cameras worldwide. He identifies four points where bias enters facial recognition, data collection, algorithmic design, feature selection and deployment, and lists specific bias types including sampling, labeling, historical, representation and algorithmic bias, illustrating algorithmic bias with a model that matched an albino wallaby to a cat based on color. He describes measuring bias with the FairFace dataset and a Department of Homeland Security study finding algorithms learn gender and race features alongside identity, and presents his company's SMU bias lab as a step toward explainability and industry-wide bias certification.https://www.youtube.com/embed/bf7NVF8xmOg16202023-05-14T00:00:00+00:00yes https://riseof.ai/talks/how-common-sense-benefits-ai-catherine-havasi/https://i.ytimg.com/vi/nvOWUrDX7FQ/hqdefault.jpgHow Common Sense Benefits AI – Catherine Havasi (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, Dr. Catherine Havasi, Chief Strategy Officer and co-founder of Luminoso, explains how adding common sense knowledge to machine learning systems helps them generalize from far less data. She argues deep learning's reliance on huge datasets, such as AlphaGo needing about 68 million self-play games without transferring anything it learned to chess, is a core limitation, especially where data cannot be simulated, as with text or robotic picking. She describes how humans generalize from very few examples by using base knowledge and analogy, and presents common sense reasoning as the addition of a general knowledge base to a machine learning system to make it more flexible. She cites research projects such as ShapeNet at Princeton and Stanford, and a game-learning project at City University London, that improved performance with less training data by infusing general world knowledge. She then describes her own project, ConceptNet, a crowdsourced multilingual knowledge graph running since the late 1990s, and how her company Luminoso uses it with transfer learning to help enterprises, including the gaming company Supercell, automate customer service with far smaller amounts of domain data.https://www.youtube.com/embed/nvOWUrDX7FQ11402018-06-10T00:00:00+00:00yes https://riseof.ai/talks/how-europe-will-survive-axel-voss/https://i.ytimg.com/vi/nZ4WpleuVW4/hqdefault.jpgHow Europe Will Survive – Axel Voss (Rise of AI Conference 2025)At Rise of AI 2025 in Berlin, Axel Voss, Member of the European Parliament and a lead architect of the EU AI Act, argues that Europe faces fragmented digital markets, insufficient investment and eroding sovereignty, and that survival, not leadership, is now the realistic goal unless the bloc changes radically. He contrasts the speed and flexibility of big tech and autocratic states with the EU's slow legislative cycle of drafting, consultation and compromise, and argues national politicians still think in outdated national terms instead of pooling forces. He calls for suspending some competition law for years to let European companies merge freely, for a sovereign 'Euro Stack' digital infrastructure, and for concentrating investment in robotics, biotech and quantum computing. He is openly critical of his own AI Act, saying an internal evaluation found as many points against it as in favor, and pushes for harmonized standards, sandboxes, a risk-based approach by company size, and resolving overlaps between the AI Act, GDPR, the Digital Services Act and related laws. He also argues Europe has overreached on data protection and should shift toward a narrower concept of privacy protection instead.https://www.youtube.com/embed/nZ4WpleuVW418602025-05-21T00:00:00+00:00yes https://riseof.ai/talks/how-to-build-a-stock-market-money-printing-machine-with-ai-raul-glavan/https://i.ytimg.com/vi/2M-r7JQJas4/hqdefault.jpgHow to Build a Stock Market Money Printing Machine with AI – Raul Glavan (Rise of AI Summit 2020)At the Rise of AI Summit 2020, Raul Glavan, a quant trader speaking at his fifth Rise of AI event, explains how he builds and runs AI trading models with his own capital. He quit his job in asset management to trade full time and entered the World Championship of Forex Trading, reporting about 150% net return and a 2.3% maximum drawdown for the year at the time of the talk. He argues that building a profitable AI trading system is possible but very hard: easily accessible public data such as prices and technical indicators is highly competitive and has little predictive value, so an edge requires accurate alternative data, rigorous feature engineering, and avoiding errors like look-ahead bias. He walks through his six-step process, data sources ranging from sentiment analysis to insider trading ratios and unconventional signals like sudden LinkedIn profile changes that hint at upcoming layoffs, and his practice of building a separate model per asset. He closes with audience questions on market efficiency, data infrastructure, time allocation and advice for beginners.https://www.youtube.com/embed/2M-r7JQJas418002020-11-30T00:00:00+00:00yes https://riseof.ai/talks/how-to-create-and-grow-ai-ecosystems-tina-kl-wer/https://i.ytimg.com/vi/qyvSQsUIbZI/hqdefault.jpgHow to Create and Grow AI Ecosystems – Tina Klüwer, Alexandra Beckstein, Thomas Neubert, Johannes Otterbach (Rise of AI Conference 2023)At Rise of AI 2023 in Berlin, a panel with Tina Klüwer (director of KIEZ, the Berlin universities' AI entrepreneurship center), Alexandra Beckstein (co-founder and CEO of QAI Ventures), Thomas Neubert (founder of the Transatlantic AI eXchange, formerly at Intel) and moderator Johannes Otterbach (VP at Merantix Momentum) discusses how to build and grow AI ecosystems in Europe. Klüwer contrasts the individual, deep-dive culture of academic research with the fast, collaborative but shallower startup ecosystem, and argues both need exchange to succeed. Beckstein describes building a quantum and AI hub in Basel, Switzerland, where her venture fund gives startups corporate-partner projects, mentoring and hardware access, and flags that Europe has only two quantum-focused VC firms and just one fund investing in AI startups from Series C onward. Neubert traces his experience bringing Silicon Valley graphics technology to market and building the Transatlantic AI eXchange from a hobby into a network of over 8,500 followers and 25 events in two years. The panel discusses Europe's market fragmentation, the need to attract and retain talent, the balance between innovation and regulation, and the cultural mindset shift needed for European AI founders to take more risks.https://www.youtube.com/embed/qyvSQsUIbZI26402023-05-14T00:00:00+00:00yes https://riseof.ai/talks/how-to-operationalize-ai-christian-kirschniak/https://i.ytimg.com/vi/-B596hVQV-Q/hqdefault.jpgHow to Operationalize AI – Christian Kirschniak (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Christian Kirschniak, a partner at PricewaterhouseCoopers who previously spent years working with AI at IBM, shares his experience taking AI from concept to real enterprise outcomes. He describes a typical pattern: a business person and a data scientist prototype an idea such as a recommendation engine, then struggle to operationalize it once IT, platform choice and data governance questions arise, often producing what he calls "POC hell," dozens of proofs of concept costing hundreds of thousands of dollars without production use. He argues the biggest recurring problem is sourcing the right data inside the enterprise, and that people, culture and governance matter as much as technology and data, including an underappreciated shortage of data engineers relative to data scientists. He highlights process-first thinking in European, brick-and-mortar companies as a barrier to treating data as an asset, and stresses accepting failure and selecting ideas by defined value rather than novelty. He summarizes these interlocking factors as an "AI molecule" and argues organizations must think holistically and involve everyone to succeed.https://www.youtube.com/embed/-B596hVQV-Q13202019-07-16T00:00:00+00:00yes https://riseof.ai/talks/how-to-put-ai-to-work-in-different-industries-wolfgang-hildesheim/https://i.ytimg.com/vi/vGOrbKWZQPo/hqdefault.jpgHow to Put AI to Work in Different Industries – Wolfgang Hildesheim (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Wolfgang Hildesheim, Director of Watson, Data Science and Artificial Intelligence DACH at IBM, walks through client projects IBM ran in Germany, Switzerland and Austria over the previous two years, opening with Deep Blue's win over Garry Kasparov and IBM Watson's 2011 Jeopardy victory as milestones before today's systems. He shows Project Debater, an IBM system that argued both sides of a policy question against human debate champion Harish Natarajan, then organizes commercial AI into four capability groups: conversational assistants, visual recognition, document understanding, and speech-to-text. Case studies include a dental insurer's chatbot that reportedly doubled sales, Austrian startup Anyline's license-plate recognition, a multi-year in-car assistant built with Mercedes-Benz covering more than 300 topics across several model lines, a document-understanding tool that finds expiring contracts among millions of PDFs, and CIMON, a floating AI companion robot developed with the German Aerospace Center and Airbus for the International Space Station. He closes on IBM's Watson OpenScale tool for monitoring AI fairness and transparency, IBM's GDPR-compliant Frankfurt data center, and practical advice for companies starting AI projects: move fast in small steps, invest in data and people, and pick partners who protect data and intellectual property.https://www.youtube.com/embed/vGOrbKWZQPo16202019-07-15T00:00:00+00:00yes https://riseof.ai/talks/how-to-scale-and-internationalize-ai-companies-ragnar-kruse/https://i.ytimg.com/vi/rdcF-JJPyrM/hqdefault.jpgHow to Scale and Internationalize AI Companies – Ragnar Kruse (Rise of AI Conference 2022)At Rise of AI 2022 in Berlin, Ragnar Kruse, co-founder of AI Hamburg and the Transatlantic AI eXchange and a former co-founder of Intershop, argues that European AI startups must internationalize into the US market much earlier than they typically do. Drawing on his own history building Intershop and a later advertising-technology company that generated 65% of its revenue in the US while employing 160 people in Hamburg, he presents figures from a PricewaterhouseCoopers study estimating AI could add over 15 trillion dollars to the global economy and roughly 11% to German GDP this decade, compared with a projected 26% gain in China. He describes AI Hamburg, a community of more than 700 members, the AI for Germany initiative with Applied AI in Munich, and a four-city German AI startup hub network built to help startups think in scalable products rather than one-off projects or proofs of concept. Kruse's central recommendation is that European AI startups should look past neighboring European markets and prioritize expanding into the US, provided they first have real local market fit, an English-language operating model and a concrete internationalization plan.https://www.youtube.com/embed/rdcF-JJPyrM19202022-06-13T00:00:00+00:00yes https://riseof.ai/talks/how-to-start-an-ai-first-company-erik-pfannm-ller/https://i.ytimg.com/vi/sd8tpyBcESo/hqdefault.jpgHow to Start an AI-First Company – Erik Pfannmöller (Rise of AI Virtual Chat 2020)At a Rise of AI Virtual Chat in 2020, Erik Pfannmöller, CEO and founder of Solvemate, discusses how to start an AI-first company with host Fabian Westerheide. Pfannmöller describes moving from a background as a competitive athlete and founder of an e-commerce company to spending a full year in 2014-15 self-teaching machine learning, from reading Peter Norvig's textbook to attending meetups, before an idea emerged from helping his father with an email problem. He explains Solvemate's path from an Excel-based concept to a viral Facebook Messenger animal-guessing game that proved the underlying algorithm worked, calling this step "algorithmic fit," which he argues should precede product-market fit. He describes it taking one and a half years to launch a first product and two years to reach a first paying customer, and advises raising three times the funding founders think they need. He argues the label "AI-first" is largely irrelevant compared with whether a company solves a real business problem, and describes Solvemate's own approach of combining rule-based dynamic decision trees with limited natural language processing.https://www.youtube.com/embed/sd8tpyBcESo36002020-05-04T00:00:00+00:00yes https://riseof.ai/talks/how-to-successfully-implement-ai-in-manufacturing-thibault-de-assi/https://i.ytimg.com/vi/ZZGgOs4xMFM/hqdefault.jpgHow to Successfully Implement AI in Manufacturing – Thibault de Assi (Rise of AI Summit 2020)At Rise of AI Summit 2020, Thibault de Assi, General Manager and Global Head of Industrial Computing at Siemens Digital Industries Factory Automation, presents Siemens' approach to deploying AI on the factory shop floor. He opens with figures on the scale of the opportunity: 85 percent of potential industrial assets remain unconnected, 87 percent of machine learning projects never reach production, and he expects 41.6 billion industrial IoT devices within five years. He describes Siemens' stack of control layer, edge layer and cloud layer (built on MindSphere and Mendix) and walks through six client use cases spanning die-casting defect prediction, bakery visual inspection, additive manufacturing quality checks, automated guided vehicle failure prediction, beer quality optimization and PCB inspection, each with concrete before-and-after metrics such as defect-rate reductions and cost savings. He answers audience poll results showing most shop-floor customers still run only proof-of-concept AI projects, and discusses lack of trust, insufficient in-house AI expertise and keeping models updated as the top barriers to adoption, along with a typical six-to-twelve-month payback period.https://www.youtube.com/embed/ZZGgOs4xMFM18602020-11-30T00:00:00+00:00yes https://riseof.ai/talks/how-to-support-an-ai-ecosystem-christian-rickerts/https://i.ytimg.com/vi/Bn_zSPCSX_o/hqdefault.jpgHow to Support an AI Ecosystem – Christian Rickerts (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, Christian Rickerts, Berlin's Secretary of State for Digitization, describes how the city government supports its AI and tech startup ecosystem after years of economic stagnation. He cites 3.1 percent GDP growth in 2017, the fourth consecutive year Berlin outperformed the German average, 50,000 to 60,000 new residents arriving annually, and one in eight new jobs created in tech. He says 69 percent of all German venture capital, about 3 billion euros across 233 deals in 2017, went to Berlin, and counts about 200 startups working in deep learning, machine learning and natural language processing in Berlin and Brandenburg. He describes the city's support instruments, including its state-owned investment bank IBB, funding programs, the Einstein Center founded in 2016, and the Adlershof research campus. Quoting Stephen Hawking's warning that AI could be civilization's greatest success or its last, Rickerts argues Berlin should also lead on data protection, privacy, taxation and algorithmic transparency, drawing an extended analogy to how traffic regulation evolved gradually alongside the automobile, from no rules at all to today's near-global system.https://www.youtube.com/embed/Bn_zSPCSX_o6002018-06-10T00:00:00+00:00yes https://riseof.ai/talks/how-to-turn-your-ideas-in-ai-into-products-ulrich-schmidt/https://i.ytimg.com/vi/ICt0RVdoV-8/hqdefault.jpgHow to Turn Your Ideas in AI Into Products – Ulrich Schmidt (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Ulrich Schmidt, Segment Manager at EBV Elektronik, a semiconductor distributor, explains how his company helps customers turn AI ideas into products running on real hardware, from microcontrollers up to FPGA-based accelerators. He describes EBV as a roughly two-billion-dollar distributor of active semiconductor components with about 1,000 employees and 370 million parts in inventory, serving mainly mid-sized industrial, automotive and smart-consumer customers across 59 offices in Europe, Africa and Russia. He surveys where customers apply AI, including retail shelf monitoring, manufacturing predictive maintenance, medical image diagnosis, financial anomaly detection and assisted driving, then walks through AI-relevant product lines from three key suppliers: NXP's edge microcontrollers and crossover processors, Xilinx's FPGA accelerator cards for data centers, and STMicroelectronics' toolchain for converting trained models onto microcontrollers. He frames EBV's own role as focused on edge inference of pre-trained models rather than the cloud-based training side of AI, closing with a short Q&A on why dedicated AI chips remain limited among the distributor's supplier lineup.https://www.youtube.com/embed/ICt0RVdoV-810802019-07-15T00:00:00+00:00yes https://riseof.ai/talks/how-to-use-ai-in-fintech-karol-przystalski/https://i.ytimg.com/vi/yQdL66kSIoQ/hqdefault.jpgHow to Use AI in Fintech – Karol Przystalski (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, Karol Przystalski, CTO of Codete, surveys use cases for AI in fintech drawn from his company's client work, while noting contractual limits on what he can disclose about specific customers. He covers fraud detection, stock market prediction, blockchain, insurance risk prediction and security applications such as face recognition, though he notes banking's heavy regulation slows adoption there. He describes Codete's open-source sentiment-analysis library, built and benchmarked against the commonly used CoreNLP library, with better results on most tested datasets, and outlines its pipeline of data cleaning, NLP-based splitting, dimensionality reduction and classification, in this case with a random forest model. He covers three types of chatbot generation (rule-based, retrieval-based and generative), an IoT insurance use case predicting driving behavior for premiums, and a library for predicting user behavior server-side to cut the number of API requests. He closes on the 'legacy model' problem: companies whose models were built years ago in now-outdated frameworks, for which Codete built an open-source converter between machine learning libraries such as TensorFlow and Keras.https://www.youtube.com/embed/yQdL66kSIoQ10802018-06-10T00:00:00+00:00yes https://riseof.ai/talks/how-universal-are-foundation-models-hans-uszkoreit/https://i.ytimg.com/vi/7bDPTWmFcN4/hqdefault.jpgHow Universal are Foundation Models? – Hans Uszkoreit (Rise of AI Conference 2023)At Rise of AI 2023, Hans Uszkoreit, Scientific Director at DFKI and co-founder and CTO of Ginance Technologies, asks why the world needs many large language models instead of one truly universal one. He explains that transformer-based foundation models gain their power from self-attention, transfer learning, self-supervised training and emergent functionality, and describes what an ideal "omniglot" model would need: fluency in most of the world's roughly 7,000 languages, where current systems handle only 20 to 50 well, plus complete factual and procedural knowledge. He argues expectations of truthfulness, creativity and consistency conflict with each other and with how these models are trained, illustrating this with contradictory ChatGPT answers about the Chinese Communist Party in Chinese versus English, and with a fabricated claim that a living friend of his had died. He describes a shift from machine learning to "machine teaching," since the core transformer algorithm has barely changed since GPT-1, and outlines two ways to add memory and multi-step reasoning: built-in recurrence, or external agents like AutoGPT. He closes arguing Germany and Europe must build their own large-model capacity through the LEAM initiative.https://www.youtube.com/embed/7bDPTWmFcN422202023-05-14T00:00:00+00:00yes https://riseof.ai/talks/how-you-could-start-your-journey-to-ai-dilek-sezg-n/https://i.ytimg.com/vi/HI8CXe7ULdo/hqdefault.jpgHow You Could Start Your Journey to AI – Dilek Sezgün (Rise of AI Summit 2020)At Rise of AI Summit 2020, Dilek Sezgün, leader of IBM's Infrastructure and AI Ecosystem for AI, big data and open source, argues that AI is not magic but a practical journey any company can start, built on data. She cites a figure that AI will contribute 16 trillion dollars to the global economy by 2030, and says most companies use only about 15 percent of their data, with 80 percent left locked and unused. She presents IBM's 'AI ladder' framework, collect, organize, analyze and infuse data, built on a hybrid cloud foundation using Red Hat OpenShift and Cloud Pak for Data, with IBM Garage as a startup-style collaboration model for developing use cases. Her core recommendation is that companies should not start with a broad AI strategy but with concrete pilot projects, building or assigning a small in-house AI team, providing broad AI training, and only then formalizing a strategy once they know what delivers value. In the closing Q&A, she says roughly 80 percent of AI effort goes into data preparation, describes tools such as automated image augmentation, addresses fear of cloud adoption among German SMEs, and stresses that ethical, transparent AI is a prerequisite for broader adoption.https://www.youtube.com/embed/HI8CXe7ULdo12602020-11-30T00:00:00+00:00yes https://riseof.ai/talks/how-you-could-use-ai-to-catalyse-sustainability-dilek-sezg-n/https://i.ytimg.com/vi/7rFTZwxvwBE/hqdefault.jpgHow You Could Use AI to Catalyse Sustainability – Dilek Sezgün (Rise of AI Conference 2023)At Rise of AI 2023 in Berlin, Dilek Sezgun, AI Techsales Leader at IBM, argues that AI is essential for companies to handle ESG (environmental, social, governance) work, which she frames as covering far more than emissions, including employee expectations, company structure and supply chains. Citing IBM Institute for Business Value research, she says 60 percent of CEOs already track their sustainability transparency, 64 percent know their sustainability goals, and 80 percent are investing in the area, while a 2021 study found 42 percent of CEOs recognize digital technology as important for sustainability. She presents IBM's model for turning sustainability ambitions into action across strategy, ESG reporting, infrastructure and supply chain, built on a data foundation she calls Cloud Pak for Data, AI models including Watson Discovery for extracting ESG data from unstructured text, and reporting and visualization tools including Cognos, Envizi and OpenPages for compliance. She identifies siloed, inconsistent and untrustworthy data as the biggest recurring obstacle, summarized as garbage in, garbage out, and closes by pointing to a six-week MVP approach IBM uses with clients, including a European bank and the energy company E.ON, and a workshop deep dive later in the program.https://www.youtube.com/embed/7rFTZwxvwBE12002023-05-14T00:00:00+00:00yes https://riseof.ai/talks/humainity-innovation-challenge-finals-2020-accenture-host/https://i.ytimg.com/vi/hDj3ZjZ4BjU/hqdefault.jpgHumAInity Innovation Challenge Finals 2020 – Accenture (Host) (Rise of AI Summit 2020)At Rise of AI Summit 2020, Accenture hosts the finals of its HumAInity Innovation Challenge, a Nordic competition launched with SingularityU Nordic, Samsung, Furhat Robotics, Swedbank and Save the Children to find AI-driven solutions for mental well-being. Accenture consultants Sandy Sander and Josephine introduce the event, noting eight semi-finalist teams were narrowed to four, who now share a 20,000 euro grant and pitch updated progress before a jury for a bonus acceleration package. Breathe presents a machine-learning digital health coach using self-reflection, reporting an 18 percent stress reduction in a 30-day beta; its updated pitch adds a multilevel Bayesian model with a Gaussian process for personalized feedback. Medified, a Finnish startup represented by Valtteri, a medical student, presents cloud-based software connecting mental health patients and professionals via NLP-driven data capture, reporting Class I CE certification and hospital-district collaborations. NoStress presents an app predicting work-related stress from calendar, email, wearable and self-report data. Healper (branded on-screen as a psychologist-matching platform) presents an AI-driven booking system matching patients to psychologists, citing a database of 1,100 psychologists in Denmark. The jury, including Swedbank's Nima Gurbani and Samsung's Alexander Grimson, unanimously names Medified the winner.https://www.youtube.com/embed/hDj3ZjZ4BjU31802020-11-23T00:00:00+00:00yes https://riseof.ai/talks/human-augmentation-through-automated-conversation-analytics-michael-br/https://i.ytimg.com/vi/YKRlZTrL9Kw/hqdefault.jpgHuman Augmentation Through Automated Conversation Analytics – Michael Brehm (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Michael Brehm, founder and managing director of i2x, argues that AI should augment human workers rather than replace them, using his company's real-time conversation analytics for telesales and service agents as the example. He traces the idea to his previous company, rebate networks, where 2,500 of 10,000 employees were telesales agents he struggled to manage. Citing OECD data, he argues the common fear that automation destroys jobs is backwards: countries with more robots and technology have lower unemployment, not higher, contradicting 1990s predictions. He argues the real risk is not job loss but a widening gap between high-tech nations, which benefit from automation, and developing nations that lose the path of industrializing through basic manufacturing. Brehm describes how i2x records and analyzes every sales or service call in real time, using its own speech recognition, to give agents, team leads and managers actionable feedback during, not after, a call, arguing this keeps underperforming-but-trainable agents in their jobs rather than having them let go.https://www.youtube.com/embed/YKRlZTrL9Kw13802019-07-19T00:00:00+00:00yes https://riseof.ai/talks/human-coexistence-with-machines-fabian-westerheide/https://i.ytimg.com/vi/TVRC9myAnUc/hqdefault.jpgHuman Coexistence with Machines – Fabian Westerheide (Rise of AI Conference 2016)At Rise of AI 2016 in Berlin, host Fabian Westerheide opens the event's second edition with a status update on artificial intelligence and its effect on humans. He notes the event grew from 20 attendees to about 150 in two editions, and announces he has just become the coordinator for AI at the German Startup Association, inviting AI companies to reach out for policy-level representation. He argues machine learning and AI have existed since the 1950s-70s but improved sharply through more processing power, deeper neural networks, better natural language and image recognition, and the rise of big data and the internet. He lists tasks where narrow AI already matches or beats humans, from games, drones and cars to writing emails, trading stocks, detecting fraud, and instant medical diagnosis. Drawing on roughly 250 audience answers to what makes humans unique, he argues traits like creativity or planning are already replicated by machines, while consciousness, emotions and ethics remain unsolved. He closes with a "wealth index" showing rising lifespan and wealth and falling working hours since industrialization, concluding AI should not be feared.https://www.youtube.com/embed/TVRC9myAnUc9002016-08-25T00:00:00+00:00yes https://riseof.ai/talks/hype-meets-reality-stefan-wess/https://i.ytimg.com/vi/CDp7iVekx1A/hqdefault.jpgHype Meets Reality – Stefan Wess (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, Stefan Wess, CEO of Empolis, argues that today's AI hype is only the latest wave of a much older story. He opens with two predictions of human-level machine intelligence, made by Herbert A. Simon in 1965 and Marvin Minsky in 1970, and shows on Google Trends that current interest is still below the 2004 peak. Drawing on his own path from case-based reasoning research to building Empolis, a company spun off from the German Research Center for Artificial Intelligence in 1991 that now serves about 700,000 professional users and 40 million customers, he insists there is no general artificial intelligence today and treats the term mainly as a marketing label for machine learning. He walks through where classic, knowledge-driven AI and newer, data-driven sub-symbolic AI each work well, and names data availability, data quality and bias, and explainability as the three real obstacles to deploying AI in enterprises. He closes by calling for hybrid, "grey box" AI and redefining AI as augmented intelligence that helps humans decide better.https://www.youtube.com/embed/CDp7iVekx1A13802018-06-10T00:00:00+00:00yes https://riseof.ai/talks/i-want-to-implement-ai-now-what-rick-newman/https://i.ytimg.com/vi/VNv9Oky_7qQ/hqdefault.jpgI Want to Implement AI, Now What? – Rick Newman (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, Rick Newman, IBM's worldwide AI sales leader, argues that organizations should start AI projects with a narrow, proven use case rather than attempting to transform an entire company at once. He illustrates the power and risk of predictive models with an example, based on a real case, in which a bank used historical loan data to flag customers likely to divorce, and therefore likely to default, with about 80 percent certainty. Citing IDC and Gartner research, he says 80 percent of a data scientist's time typically goes into preparing data, and describes IBM tools built to automate that work, including one that let a non-specialist build a cancer-cell detection model reaching 95 percent accuracy in hours. He argues machine learning remains essential for traceability in regulated settings such as financial services, and describes IBM's NVLink-based Power CPUs and distributed deep learning cutting a breast-cancer research customer's training window from days to hours. He closes with an insurance example from his own life and a warning against proprietary, non-portable technology.https://www.youtube.com/embed/VNv9Oky_7qQ12002018-06-10T00:00:00+00:00yes https://riseof.ai/talks/industrial-applied-ai-at-siemens-ulli-waltinger/https://i.ytimg.com/vi/1Vs7NQZ77xs/hqdefault.jpgIndustrial Applied AI at Siemens – Ulli Waltinger (Rise of AI Virtual Chat 2020)At the Rise of AI Virtual Chat in 2020, Fabian Westerheide interviews Dr. Ulli Waltinger, head of Siemens' Machine Intelligence Research Group and technology head of the Siemens AI Lab, about industrial applied AI. Waltinger explains that after the big-data hype and a second AI hype, Siemens' management set up a top-down program called Company Core Technologies with an analytics-and-AI track of around 200 to 230 researchers, trained managers company-wide on core concepts, and placed application centers close to business units such as mobility, energy and healthcare so AI teams work directly with customers. He describes roughly 80 percent of proof-of-concept projects stalling before production, and names C-level sponsorship, early involvement of operations staff, and including customers from the start as the factors that raise the odds of a project reaching deployment. He then explains why trust and robustness matter more in B2B industrial AI than in consumer AI, since industrial systems increasingly make autonomous decisions with physical and financial consequences, and describes Siemens' techniques for measuring model robustness and explainability, including domain-adaptation scoring, Bayesian graphical models and rule-based approximations of black-box models.https://www.youtube.com/embed/1Vs7NQZ77xs36602020-08-27T00:00:00+00:00yes https://riseof.ai/talks/industry-ai-physical-ai-autonomous-enterprises-feiyu-xu/https://i.ytimg.com/vi/uI_OsZWVMPU/hqdefault.jpgIndustry AI, Physical AI & Autonomous Enterprises – Feiyu Xu (Rise of AI Conference 2026)At Rise of AI 2026 in Berlin, Feiyu Xu of the German University of Digital Science argues that AI is entering a new phase, moving beyond software chatbots into manufacturing, infrastructure and energy systems as industry AI and physical AI. She cites Jeff Bezos reportedly planning to raise 100 billion US dollars to buy and transform existing manufacturing companies with AI as a sign of how fast this shift is happening. Xu distinguishes industry AI, which covers the end-to-end enterprise value chain, from physical AI, which adds sensors, three-dimensional context and time series data, and describes three levels of autonomous enterprises: AI as advisor, AI as operator, and AI as orchestrator. Entrepreneur Patrick then presents the GDPval benchmark, showing AI models closing the gap with human experts on real enterprise tasks, and demonstrates how AI agents can be manipulated through social engineering rather than classic prompt injection. A Q&A covers multi-agent oversight, model differences in resisting social engineering, and the gap between companies' AI ambitions and actual implementation.https://www.youtube.com/embed/uI_OsZWVMPU19802026-07-15T00:00:00+00:00yes https://riseof.ai/talks/innovating-regulation-to-boost-bavarian-leadership-in-ai-fabian-mehrin/https://i.ytimg.com/vi/Jbp7gyB96cY/hqdefault.jpgInnovating Regulation to Boost Bavarian Leadership in AI – Fabian Mehring (Rise of AI Conference 2024)At Rise of AI 2024 in Berlin, Fabian Mehring, Bavaria's Minister of Digital Affairs, argues that Bavaria wants to become a leading AI hub and that smarter regulation, not less regulation, is the way to get there. He cites Bavaria's Hightech Agenda, which will channel 5.5 billion euros by 2027 into more than 34 new AI professorships, over 10,000 new AI-focused student places, new research centers, and a Franconian university built entirely around AI. He points to a new strategic partnership with Aleph Alpha, including a data center and new offices in Munich, and to concrete public projects such as AI-based early detection of heart attacks in women and an AI-driven early-warning system for storms and floods. He warns that the EU AI Act risks becoming a bureaucratic burden like GDPR, citing a Bitkom finding that over 60% of German businesses see GDPR as stifling innovation, and proposes a 'Bavarian Innovation Accelerator', a protected legal sandbox plus investor training and certification standards, modeled partly on France's capital-mobilization success under President Macron.https://www.youtube.com/embed/Jbp7gyB96cY8402024-05-20T00:00:00+00:00yes https://riseof.ai/talks/introduction-to-rise-of-ai-2016-fabian-westerheide/https://i.ytimg.com/vi/vPxYmTW1SzA/hqdefault.jpgIntroduction to Rise of AI 2016 – Fabian Westerheide (Rise of AI Conference 2016)At Rise of AI 2016 in Berlin, an event for 100 selected guests, host Fabian Westerheide opens the evening by asking what the singularity actually means. He recounts a novel in which an email company's team builds a smarter reply feature using natural language processing and neural networks, and notes that Google shipped a comparable real feature, Smart Reply, in 2015, arguing that fictional AI technologies tend to become real within one to three years. Drawing on the blog Wait But Why, he offers three definitions of the singularity: computers matching or exceeding human performance, humans losing control of their own creation, or people simply believing a machine is superior to them. He argues humans build AI because they are lazy and want more output for the same effort. He then presents 21 jobs the audience named in advance as most at risk from automation, grouped from low-paid routine roles to professional, analytical and office jobs, while arguing that work built on emotion, free thinking and creativity is safer because science does not yet understand how those capacities arise.https://www.youtube.com/embed/vPxYmTW1SzA4802016-02-28T00:00:00+00:00yes https://riseof.ai/talks/is-ai-evil-carla-hustedt/https://i.ytimg.com/vi/ofZHg0YY2AU/hqdefault.jpgIs AI Evil? – Carla Hustedt (Rise of AI Conference 2022)At Rise of AI 2022 in Berlin, Carla Hustedt, head of the Digital Center at Stiftung Mercator, argues that the real risk from AI is not a sentient, rebelling superintelligence but already powerful humans using the technology as a tool to consolidate power and deepen inequality. She groups the human causes of 'evil AI' into three categories, illustrated with case studies: AI used for openly harmful purposes, citing China's mass surveillance and detention of Uyghurs since 2013 through systems like the Integrated Joint Operations Platform; AI used for profit at the expense of human rights, citing Frances Haugen's revelations that Facebook knowingly steered young users toward toxic content; and AI used with good intentions but badly, citing the Dutch tax authority's self-learning fraud-detection system, which wrongly accused about 26,000 families, disproportionately from migrant backgrounds, and triggered the resignation of the Dutch cabinet in 2021. Hustedt then presents solutions she funds through philanthropy: more diverse tech teams, civil society organizations such as AlgorithmWatch, transparency registers like Amsterdam's algorithm register, and the EU's risk-based AI regulation.https://www.youtube.com/embed/ofZHg0YY2AU15002022-06-13T00:00:00+00:00yes https://riseof.ai/talks/is-it-possible-to-create-strong-ai-helmut-linde/https://i.ytimg.com/vi/dEa70cASqK8/hqdefault.jpgIs It Possible to Create Strong AI – Helmut Linde (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Helmut Linde, Global Head of Data Science at Merck KGaA, argues that the path toward Strong AI runs through solving the problem of invariant representations. He compares today's algorithms with biological intelligence, noting that a small child can recognize a cat from only a few examples, that a person recognizes a song regardless of which instrument or key it is played in, and that a story is recognized whether it appears as a film, an audio play or a book. Brains, he argues, can form invariant representations of real-world entities across very different sensory inputs, something current machine learning algorithms cannot yet do. He states that this gap, rather than raw performance on narrow benchmarks, is the key obstacle to progress toward Strong AI, and that the brain can serve as an inspiration for a next generation of learning algorithms. Although there is still very limited understanding of the brain's underlying computational principles, Linde argues there is reason to hope this biological algorithm can be reverse-engineered, which he says requires a genuinely interdisciplinary effort spanning neuroscience, computer science, mathematics and physics.https://www.youtube.com/embed/dEa70cASqK818002019-07-17T00:00:00+00:00yes https://riseof.ai/talks/k-i-t-t-i-need-you-buddy-holger-weiss/https://i.ytimg.com/vi/l_onHpZkCsQ/hqdefault.jpgK.I.T.T. – I need you, buddy – Holger Weiss (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, Holger Weiss, CEO of German Autolabs, argues that voice assistants will have their biggest impact not at home but in the car, where drivers cannot look at a screen. He introduces Chris, a retrofit conversational co-driver that connects to a phone via voice and gesture control, built because most cars on the road are old: the average German car is ten years old, and Germany has 47 million cars while the US has 220 million, so a new-car-only assistant would take years to reach the market. Weiss cites growing distraction-related deaths, including the US 'Snapchat effect', and ADAC data on smartphone-related traffic deaths to argue for hands-free interaction. He distinguishes a co-driver from a home assistant like Alexa or Siri: it must understand context such as location, speed, connectivity gaps and cognitive load, and prioritize accordingly, for example not reading an email while a driver approaches a difficult highway exit. German Autolabs worked with the German Ministry of Transport and a Munich traffic psychology professor on modeling driver cognitive load. Chris launched as a pre-order device priced at 299 euros or dollars, in German and English.https://www.youtube.com/embed/l_onHpZkCsQ11402018-06-13T00:00:00+00:00yes https://riseof.ai/talks/ki-park-ai-can-improve-our-lives-we-are-working-on-it-oliver-salzmann/https://i.ytimg.com/vi/8mFSA_CKlTk/hqdefault.jpgKI Park: AI Can Improve Our Lives, We Are Working on It – Oliver Salzmann, Alexander Rinke, Rupprecht Rittweger (Rise of AI Summit 2020)At Rise of AI Summit 2020 in Berlin, a panel with Oliver Salzmann, Managing Director of KI Park, Alexander Rinke, Co-CEO and co-founder of Celonis, and Robert Vega, who represents Investa and chairs NTT's EMEA data center division, launches KI Park, a non-profit initiative meant to connect Germany's AI founders, researchers, corporates and policymakers in one collaborative ecosystem. Salzmann argues that while AI today delivers most value through process efficiency in engineering and automotive-heavy German industry, about 80 percent of companies will buy AI solutions from and partner with startups going forward, and that Germany's engineering talent needs a shift from competitive, IP-protective thinking to open collaboration. Vega describes Investa and NTT's plan to dedicate part of Berlin's roughly 360,000-square-meter Marienpark site to flexible startup workspaces, autonomous-driving test tracks and what is planned to become Europe's largest data center. Rinke describes Celonis's contribution to AI education across technical, digital, business and ethics skills through an academic alliance of over 400 universities and research institutions, opened to everyone in Germany through KI Park. The panel closes on what it calls for: courage, boldness and speculative investment from companies, startups and government alike.https://www.youtube.com/embed/8mFSA_CKlTk18602020-11-30T00:00:00+00:00yes https://riseof.ai/talks/large-ai-models-in-a-global-perspective-hans-uszkoreit/https://i.ytimg.com/vi/IT9pBZ3fUd0/hqdefault.jpgLarge AI Models in a Global Perspective – Hans Uszkoreit (Rise of AI Conference 2022)At Rise of AI 2022 in Berlin, Hans Uszkoreit compares AI development in the US, China and Europe and argues that Germany is falling further behind unless it changes how it funds applied research. He explains how large language models such as GPT-3 use self-attention to process long stretches of text at once and are trained through self-supervised learning, producing fluent, humanlike text while still failing at multi-step logical reasoning. Using a six-criteria survey, he shows the US leading in talent, research, development and hardware, China leading in adoption and data, and the EU trailing both. He credits the US lead in applications to DARPA-style funding, competitive parallel research contracts, infrastructure projects, procurement and sustained funding, contrasting this with German programs that fund topics only once and switch focus too quickly. He cites German-born researchers who achieved their breakthroughs after moving to the US, reviews Germany's underfunded national AI strategy, and presents the "Large European AI Models" initiative, backed by about 400 companies, as a step toward closing the gap.https://www.youtube.com/embed/IT9pBZ3fUd020402022-06-13T00:00:00+00:00yes https://riseof.ai/talks/learning-from-data-but-not-labels-jakob-uszkoreit/https://i.ytimg.com/vi/GQhL9Lkv-YQ/hqdefault.jpgLearning from Data but Not Labels – Jakob Uszkoreit (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Jakob Uszkoreit, a deep learning researcher at Google Brain, argues that supervised learning will not scale to the complexity of problems AI should eventually solve, because it requires ever more complex and expensive labeled data, and because some domains, such as rare conditions in medical imaging, offer too few examples of any single case. He presents self-supervised learning as an alternative inspired by how humans learn by observation, centered on BERT, a bidirectional Transformer model trained by predicting words deleted from large text corpora. Built on the Transformer, an architecture his team began developing around 2017, and on Google's TPU hardware, BERT set new results on a range of natural language understanding benchmarks and slightly exceeded human performance on the Stanford Question Answering Dataset after fine-tuning, despite Uszkoreit stressing it does not understand the world. He then describes early Google research work extending self-supervision beyond text to video, including a model that learns to recolorize black-and-white footage by implicitly tracking objects, and a Berkeley robot-arm project used to train models to predict video continuations and basic physical interactions.https://www.youtube.com/embed/GQhL9Lkv-YQ19202019-07-17T00:00:00+00:00yes https://riseof.ai/talks/legal-frontiers-navigating-ai-integration-in-the-business-world-inka-k/https://i.ytimg.com/vi/Yb5yUGnmTrE/hqdefault.jpgLegal Frontiers: Navigating AI Integration in the Business World – Inka Knappertsbusch (Rise of AI Conference 2024)At Rise of AI 2024, on the Applied AI Stage, Inka Knappertsbusch, Counsel at CMS Germany, addresses the legal challenges and opportunities that arise when businesses integrate AI into their operations. According to the talk's description, she covers the regulatory landscape businesses face as they adopt AI technologies, the compliance requirements that come with it, and best practices for navigating this integration. No usable transcript is available for this recording because speech recognition failed, so no direct account of her specific arguments, examples, case references or the particular legal frameworks she names can be given here. What is documented in this record is drawn solely from the session's official YouTube description rather than from the talk itself. The session was part of Rise of AI's Applied AI Stage program. Readers seeking the substantive legal analysis, specific regulations discussed, or practical recommendations Knappertsbusch gives should consult the original recording directly, since none of that content could be verified from the material available for this summary.https://www.youtube.com/embed/Yb5yUGnmTrE11402024-05-21T00:00:00+00:00yes https://riseof.ai/talks/lessons-learnt-from-the-nordic-ai-ecosystem-christian-guttmann/https://i.ytimg.com/vi/Rx4QMu3nKs8/hqdefault.jpgLessons Learnt from the Nordic AI Ecosystem – Christian Guttmann (Rise of AI Conference 2022)At Rise of AI 2022 in Berlin, Christian Guttmann, director of the Nordic Artificial Intelligence Institute, former VP Global Head of AI at Tieto, and a researcher at the Karolinska Institute, shares what he has learned working across Sweden, Finland, Denmark and Norway. Citing global AI rankings where Finland and Denmark place in the low teens, he attributes Nordic strengths to near-universal internet coverage, a personal-number system linking private and public data such as healthcare records, and high public trust in data sharing, illustrated by Klarna's payment-risk models, cross-registry healthcare analytics he worked on, and Iceland's national DNA biobank. He describes government-backed structures such as Nordic Innovation Houses and the Nordic Council of Ministers, an engineering-heavy but talent-exporting workforce, early technology adoption, and English used as the default business language from day one. He also notes friction points, including state alcohol monopolies and diverging cloud policies between Sweden and Finland, before surveying large companies and startups applying AI, and closing with recommendations for startups, investors and politicians, including a call for a more ambitious, JFK-style AI vision.https://www.youtube.com/embed/Rx4QMu3nKs817402022-06-13T00:00:00+00:00yes https://riseof.ai/talks/let-s-give-ai-some-hope-florian-dohmann/https://i.ytimg.com/vi/qDhbxKnQIMk/hqdefault.jpgLet’s Give AI Some Hope – Florian Dohmann (Rise of AI Conference 2023)At Rise of AI 2023 in Berlin, Florian Dohmann, founder and Chief Creative at Birds on Mars GmbH, argues that today's generative AI moment is better understood as the start of a broader cultural shift he calls "generation AI" rather than just a technology hype cycle. He traces his own journey from a 2017 project with painter Roman Lipsky, an "artificial muse" that used a pretrained neural network to extract patterns from the painter's digital works, through a 2019 moment when Alphabet CEO Sundar Pichai publicly praised one of the resulting paintings. Dohmann argues the field talks too much about AI tools ("hammers") and too little about the problems worth solving, illustrating this with a Berlin city project that uses classical, non-generative AI to predict which street trees need watering based on soil and shadow data. He rejects the word "hope" as too passive, calling instead for positive visions, entrepreneurship, empathy and interdisciplinary collaboration, and closes by proposing "regenerative AI" built around circular-economy principles and the launch of a regenerative AI lab.https://www.youtube.com/embed/qDhbxKnQIMk14402023-05-14T00:00:00+00:00yes https://riseof.ai/talks/liability-concerns-of-autonomous-machines-helen-tung/https://i.ytimg.com/vi/LjJkS2MEsm4/hqdefault.jpgLiability Concerns of Autonomous Machines – Helen Tung (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, legal futurist Helen Tung explores who is liable when autonomous machines cause harm, using three case studies. In a fictitious 2050 scenario, a person is told by an AI doctor that new medication will extend their life by fifty years, but that sensors predict a 99.95 percent chance of future cancer, heart disease and depression, triggering a higher insurance premium; the same person's autonomous car is then hacked, and after a crash an AI judge finds them fully liable for retaking manual control, a ruling later reduced to 25 percent liability on appeal to a human judge. A second scenario asks whether a robotic dog left 80 percent of an owner's will could hold legal entity status. A real case she describes involved two horse owners disputing which owner's horse a jockey could ride at England's Derby, resolved by judges the morning of the race. Tung then shifts to a more personal argument, invoking Clayton Christensen's theory of disruptive innovation and life-measurement questions, before leading a short guided breathing exercise and closing with a Wizard of Oz metaphor about people already possessing the intelligence, heart and courage that AI debates worry about outsourcing.https://www.youtube.com/embed/LjJkS2MEsm412602018-06-10T00:00:00+00:00yes https://riseof.ai/talks/live-love-die-repeat-from-worm-to-ai-wagner-steuer-costa/https://i.ytimg.com/vi/u_zYLjEKENY/hqdefault.jpgLive, love, die, repeat – From worm to AI – Wagner Steuer Costa (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Wagner Steuer Costa, a data scientist working in neuroscience and biochemistry, presents research on the nematode C. elegans, a one-millimeter worm with exactly 302 neurons, as a model for decision-making mechanisms that current AI systems lack. Using optogenetics, proteins controlled by light, his lab activates specific neurons and observes behavior and synaptic ultrastructure changes, showing that faster neural signaling increases both the release probability and the size, or information content, of synaptic vesicles. He describes a single neuron that decides whether the animal flees or freezes based on conflicting signals from head and tail, and shows that a distinct sleep neuron stays active for extended periods while the animal is unresponsive, only ceasing when the worm is woken by an oxygen pulse. He argues that neuromodulators, slower-acting chemicals like neuropeptides, help maintain the neural network in a state of criticality that allows fast, accurate responses to changing conditions. Steuer Costa closes by arguing that current AI approaches lack compartmentalized processing, sleep-like memory consolidation and, most provocatively, death, which he argues could be a necessary driver of intelligence through evolutionary pressure across many AI iterations.https://www.youtube.com/embed/u_zYLjEKENY15002019-07-17T00:00:00+00:00yes https://riseof.ai/talks/living-in-the-post-ai-world-charles-edouard-bou-e/https://i.ytimg.com/vi/SEvvPR6KB78/hqdefault.jpgLiving in the Post-AI World – Charles-Edouard Bouée (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Charles-Edouard Bouee, CEO of Roland Berger, revisits his 2018 thesis and reports on where AI actually stands a year later. He recaps "portable AI," a personal cloud he compares to Jiminy Cricket and to Joy from Blade Runner 2049, arguing that GAFAM and the Chinese BAT platforms are on the last stretch of their exponential growth because portable AI will eventually replace their revenue sources, while traditional companies fighting digital leaders, startups, platforms and their own IT systems have more future than they think. He says progress has been slower than he expected: every client mentions AI on earnings calls, but few actually use it, and GAFA companies mostly apply basic machine learning to harvest existing data, such as Amazon optimizing warehouse robots and server uptime, rather than building genuinely advanced AI. He argues GDPR benefits Europe by protecting the personal-cloud data that portable AI will need, and gives companies practical advice: start small, focus on real business problems, and treat cloud computing skeptically, since he estimates 95 percent of it is storage rather than processing. He closes with predictions for 2029, picturing AI as everything, everywhere, for everyone.https://www.youtube.com/embed/SEvvPR6KB7812602019-07-02T00:00:00+00:00yes https://riseof.ai/talks/making-ai-useful-thomas-schmidt/https://i.ytimg.com/vi/gKCQIAprFVk/hqdefault.jpgMaking AI Useful – Thomas Schmidt (Rise of AI Conference 2025)At Rise of AI 2025 in Berlin, Thomas Schmidt, co-founder of Amber AI, an Nvidia elite partner founded in 2006, argues that the industry must move from AI hype to real, useful impact. He traces the field from AlexNet in 2012 through Nvidia's 2016 shift into AI-focused hardware and the 2022 ChatGPT moment, citing figures that generative AI returns 3.5 US dollars per dollar spent on average, and up to 8 times for the best-performing companies. He argues much enterprise infrastructure is still outdated CPU-based hardware, and that moving to current-generation GPUs, especially Nvidia's Blackwell architecture, cuts power use and cost while shifting workloads from training toward inference. Schmidt presents a human-centric design framework for making AI actually get used inside companies, emphasizing starting from real business pain points rather than technology demos, and describes three concrete use cases: accelerating patent-lawyer document review, optimizing logistics and cargo loading, and using computer vision to identify chick sex in eggs before hatching to stop unnecessary culling. He closes with a call to prioritize trust, impact and workflow integration over model sophistication.https://www.youtube.com/embed/gKCQIAprFVk15002025-05-21T00:00:00+00:00yes https://riseof.ai/talks/micropsi-industries-ai-for-industrial-robots-ronnie-vuine/https://i.ytimg.com/vi/VWXc7_w0Q7k/hqdefault.jpgMicropsi Industries: AI for industrial robots – Ronnie Vuine (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Ronnie Vuine, CEO of Micropsi Industries, argues that giving AI a body helps ground symbols in real experience, which is why his company connects AI to industrial robots. He contrasts traditional industrial robotics, where movements are fully predetermined and synchronized geometrically, for example welding on an Audi production line, with tasks that require perception, such as plugging in a cable, which conventional robots can only do with expensive 3D cameras and precise point-cloud model fitting. Micropsi's product, Mirai, instead lets a person guide a collaborative robot by hand through a movement while a camera records it, and sends that data to the cloud, which returns a policy for real-time, vision-guided corrective movement. He demonstrates this with a Liebherr fridge factory case, where a robot learns to find soldering points to sniff for coolant leaks, and explains that the underlying product is a general hand-eye coordination tool, not specific to that niche. Vuine explains why the company avoids reinforcement learning, relying instead on recorded real-world demonstrations, and answers audience questions on transferring the approach to other machines and on sensor choice.https://www.youtube.com/embed/VWXc7_w0Q7k13802019-07-18T00:00:00+00:00yes https://riseof.ai/talks/military-ai-in-europe-not-smart-enough-ulrike-franke/https://i.ytimg.com/vi/TBGSUvgMn2Q/hqdefault.jpgMilitary AI in Europe – Not Smart Enough? – Ulrike Franke (Rise of AI Summit 2020)At the Rise of AI Summit 2020, Dr. Ulrike Franke, a policy fellow at the European Council on Foreign Relations, argues that military AI deserves more public attention in Europe than it currently gets. She makes four points: AI is already used across intelligence analysis, logistics, cyber operations, command and control and drone swarming, with roughly two-thirds of US Department of Defense AI-related investment going into AI-enabled systems; civilian and military AI are not cleanly separable, as shown by the 2017 controversy over Project Maven, a US Pentagon-Google cooperation on drone footage analysis; AI could fundamentally affect warfare and global stability, including risks to nuclear deterrence if AI-enabled sensors make oceans 'transparent' to submarine detection, and risks of rapid 'flash wars' between interacting autonomous systems; and Europe's political sphere remains reluctant to discuss military AI publicly, with France as the notable exception. She closes a Q&A on AI proliferation to non-state actors and the drone-heavy conflict in Nagorno-Karabakh by calling for European governments to discuss military AI more openly.https://www.youtube.com/embed/TBGSUvgMn2Q18602020-11-23T00:00:00+00:00yes https://riseof.ai/talks/multimodal-contrastive-learning-baran-avinc/https://i.ytimg.com/vi/ql2IZhPd9Pc/hqdefault.jpgMultimodal Contrastive Learning – Baran Avinc (Rise of AI Conference 2023)At Rise of AI 2023 in Berlin, Baran Avinc, Data Science Architect at SVA System Vertrieb Alexander GmbH, delivers a keynote titled "Multimodal Contrastive Learning." This page is built entirely from the conference's program metadata, because the video's automatically generated transcript failed for this recording and no usable spoken-word content could be recovered from it. The only verifiable information available is the talk's title, the speaker's name, his stated role and employer, the conference edition and year, and the roughly 22-minute duration. No further YouTube description text, no chapter markers, and no other contextual material beyond the title and speaker credit were provided in the source material used to build this page. Consequently, this record cannot summarize the talk's specific arguments, examples, data, or conclusions, and none have been inferred or added from outside knowledge of the topic. Readers who need the substantive content of the talk should consult the original video directly, since the automated speech-recognition transcript that would normally support this page is not usable for "Multimodal Contrastive Learning" by Baran Avinc at Rise of AI 2023.https://www.youtube.com/embed/ql2IZhPd9Pc13202023-05-14T00:00:00+00:00yes https://riseof.ai/talks/navigating-the-ai-arms-race-in-defense-yvonne-hofstetter/https://i.ytimg.com/vi/oynjjwu8VZw/hqdefault.jpgNavigating the AI Arms Race in Defense – Yvonne Hofstetter, Michael Vetter, Ulrike Franke, Katja Munoz (Rise of AI Conference 2024)At Rise of AI 2024 in Berlin, a panel with Yvonne Hofstetter (CEO, 21strategies), Lieutenant General Michael Vetter (CIO, German Federal Ministry of Defense) and Ulrike Franke (Senior Policy Fellow, European Council on Foreign Relations), moderated by Katja Munoz, discusses how Germany can not just keep up but thrive in AI-driven warfare. Using a moonshot-style format, the panel first reviews the status quo: Vetter describes the Bundeswehr's new digitization platform and projects such as the digitized battlefield, an electronic-intelligence AI laboratory and a common operational picture; Hofstetter argues defense AI has changed little in 25 years and that information dominance alone is not enough, citing Ukraine; Franke says the Bundeswehr has been underfunded for decades and is now rebuilding everything at once, making a formal military AI strategy less urgent than actually building capability. The panel then sets two- and five-year visions covering drone swarms, autonomy rules, procedures for AI targeting recommendations, software-defined defense, and Germany's Defense Metaverse test environment, before naming what each considers most necessary to achieve them.https://www.youtube.com/embed/oynjjwu8VZw27602024-05-20T00:00:00+00:00yes https://riseof.ai/talks/neustaat-digitizing-government-thomas-heilmann/https://i.ytimg.com/vi/lRaF-6UnGjw/hqdefault.jpgNEUSTAAT: Digitizing Government – Thomas Heilmann (Rise of AI Virtual Chat 2020)At a Rise of AI Virtual Chat in 2020, Thomas Heilmann, member of the German Bundestag, discusses his book NEUSTAAT with host Fabian Westerheide. Heilmann describes NEUSTAAT as more than 100 concrete reform proposals for digitizing and modernizing German government, developed over a year and a half of research by a working group that traveled to China and South Korea to study what makes societies more innovative. He argues the German government proved surprisingly fast and effective during the Corona crisis when focused on a single topic, and that the pandemic forced schools, courts and parliament to adopt digital tools that existing law already allowed but no one had executed. He proposes a state-backed retirement fund invested globally by an independent agency, university investment funds modeled on MIT, and European Investment Bank backing for startup IPOs to address Europe's lack of late-stage funding and exits. He also outlines a "future lobby" to represent not-yet-existing industries in lawmaking, data auditors who would certify how companies use personal data, and a risk-based approach to AI regulation, arguing that clear rules, not the absence of regulation, help businesses invest with confidence.https://www.youtube.com/embed/lRaF-6UnGjw36602020-06-29T00:00:00+00:00yes https://riseof.ai/talks/no-one-should-trust-ai-joanna-bryson/https://i.ytimg.com/vi/YgZD74jIMJY/hqdefault.jpgNo one should trust AI – Joanna Bryson (Rise of AI Conference 2023)At Rise of AI 2023 in Berlin, Joanna Bryson argues that no one should trust AI and that AI should instead be built to be auditable. She defines trust as a relationship between peers who choose not to micromanage each other because they expect fair treatment, illustrating this with the economic trust game, where a society's trust rises and then collapses once partners start defecting. Robots, she says, are not peers: they are designed and owned artefacts, best understood as parts of corporations embedded in people's homes, so societies build governance structures, such as the EU, to keep those corporations in line rather than trusting individual machines. She walks through intelligence as a subset of computation constrained by time, space and energy, and stresses that AI depends on physical infrastructure, not only data and algorithms, pointing to Google's fibre networks and chips. She then reviews EU rules including the GDPR, DMA, DSA and the AI Act, arguing that most of what they require is documentation practice already familiar from 1980s software engineering, so responsibility can be traced when something goes wrong.https://www.youtube.com/embed/YgZD74jIMJY18602023-05-14T00:00:00+00:00yes https://riseof.ai/talks/now-that-ai-is-here-what-do-we-do-with-it-chris-boos/https://i.ytimg.com/vi/z2rbpUmcHiM/hqdefault.jpgNow That AI Is Here, What Do We Do With It – Chris Boos (Rise of AI Summit 2020)At the Rise of AI Summit 2020, Chris Boos, CEO of Arago AG, argues that AI has already arrived and the real question is what to do with it. He opens by noting that capital markets value three Silicon Valley platform companies more highly than Germany's entire publicly listed industrial economy, that revenue per employee is far higher at a company like Apple than at Volkswagen, and that employees' contribution to actual productivity has been declining for decades, evidence that the industrial era, built on standardization and economies of scale, has run its course. He estimates that with today's technology 80 percent of current work can already be automated, using implicit and explicit knowledge held in data to let machines find individual solutions rather than standardized processes. Boos gives four predictions: society must act now on environmental, populist and industrial-disruption pressures; the current adversarial system of politics, economy and society must give way to a knowledge economy; AI is already being applied in agriculture, medicine, education and mobility, but only in small steps; and Europe's own path should be humanism, distinct from US efficiency and Chinese cohesion. He closes by urging companies to stop running pilots, since the technology already works, and instead change their mindset to let AI act.https://www.youtube.com/embed/z2rbpUmcHiM16202020-11-20T00:00:00+00:00yes https://riseof.ai/talks/on-trust-and-scaling-towards-an-ai-enterprise-at-deutsche-telekom-jan/https://i.ytimg.com/vi/SCACiGfeiB8/hqdefault.jpgOn Trust and Scaling: Towards an AI Enterprise at Deutsche Telekom – Jan Hofmann (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, Dr. Jan Hofmann, Vice President at Deutsche Telekom, describes how the company built internal and external trust while rolling out AI-driven chatbots. He frames the opportunity through scale, roughly 160 million mobile customers and large volumes of repetitive processes and data, set against a mix of enthusiasm and fear inside the organization about jobs being automated away. Rather than a hidden skunkworks project, a scattered grassroots effort, or a CEO-mandated push across every department, Deutsche Telekom concentrated resources on one focus area and built trust through it, a strategy he calls the trust game. He identifies rigorous focus, fast delivery of small working products, and close day-one collaboration between R&D and business units as the three drivers that made this work, alongside publishing public AI guidelines to build trust with customers and society. He then walks through the resulting rule-based and AI customer service bots in Austria and Germany, and describes the company's next steps into AI-driven process automation and predictive analytics.https://www.youtube.com/embed/SCACiGfeiB810802018-06-10T00:00:00+00:00yes https://riseof.ai/talks/open-innovation-for-ai-adoption-marcel-otto-yon/https://i.ytimg.com/vi/-LXRDHRoQ_8/hqdefault.jpgOpen Innovation for AI Adoption – Marcel ‘Otto’ Yon (Rise of AI Virtual Chat 2020)In this Rise of AI Virtual Chat from September 2020, host Fabian Westerheide talks with Marcel 'Otto' Yon, who spent his last four years as founder and CEO of the German Armed Forces' digital innovation unit and earlier built companies in facial recognition, later used in German passports, and in image recognition for cancer detection. Drawing on roughly 50 corporate and military innovation units he has studied, Yon lays out five traits of the successful ones: a focus on execution rather than ideas, direct reporting to the CEO, positioning as an internal competitor to the core business, room to grow instead of an early handoff, and mixed teams of insiders and outside entrepreneurs. The conversation covers why German organizations move slowly compared with the US, citing accountability culture and business-to-government sales cycles of around ten years, why diversity in leadership means more than gender, how his unit built trust with soldiers, startups and allied militaries, the personal backlash he faced, and his view that AI's exponential growth will leave organizations too little time to adapt once the curve turns steep.https://www.youtube.com/embed/-LXRDHRoQ_838402020-09-24T00:00:00+00:00yes https://riseof.ai/talks/opening-state-of-ai-2023-fabian-westerheide/https://i.ytimg.com/vi/_O5MBTI7kwE/hqdefault.jpgOpening & State of AI 2023 – Fabian Westerheide (Rise of AI Conference 2023)At Rise of AI 2023 in Berlin, Fabian Westerheide, founder and CEO of Rise of AI and founding partner at Asgard Capital, opens the conference with a state-of-AI keynote, preceded by a scripted video of an AI avatar generated with ChatGPT and a text-to-video tool, standing in for host Veronica Westerheide. He welcomes over 1,200 virtual attendees from 57 nations and argues 2023's task is working with existing foundation models and generative AI rather than chasing new ones, with Europe finding its own vertical, industry-specific applications instead of competing on consumer chatbots. He frames AI as augmenting rather than replacing jobs, calls for sustainable, energy-conscious AI development, and discusses the EU AI Act, warning it could have made a tool like ChatGPT illegal in Europe. He predicts AI will widen the wealth gap and raise social tension, and argues Germany's opportunity lies in precise B2B and industrial AI rather than consumer products, since OpenAI has already won that race. The keynote closes with a conversation with Lara, host of the Applied AI stage, on the AI Act's burden on startups, data privacy risks of using ChatGPT at work, and Westerheide's expectation that AI will reach every microchip-equipped machine by 2045.https://www.youtube.com/embed/_O5MBTI7kwE16202023-05-14T00:00:00+00:00yes https://riseof.ai/talks/opening-global-ai-strategy-fabian-westerheide/https://i.ytimg.com/vi/ZzPgO5IwBk8/hqdefault.jpgOpening: Global AI Strategy – Fabian Westerheide (Rise of AI Conference 2022)At Rise of AI 2022 in Berlin, Fabian Westerheide, CEO of Rise of AI and CEO of Asgard Capital, opens the first hybrid edition since the pandemic with roughly 800 people joining online alongside the in-person audience. He recaps how the European AI ecosystem emerged from a 10-person hackerspace meetup around 2012, through waves of entrepreneurs, scientists, developers, seed capital, media attention in 2018, corporate adoption, and regulators arriving last in 2019 after the US and China had already moved. He describes a personal struggle in 2019 as the community's radical, idealistic edge gave way to suits, and recounts buying a forest outside Berlin during the pandemic, where he planted over 3,000 trees and underwent a personal transformation while his business activity fell to zero. He closes by framing 2022 around the new war involving Russia, AI's military use, the competing American and Chinese tech ecosystems, and Europe's attempt to build its own trustworthy AI standards, before moderator Christina Boesenberg asks him about the conference's sustainability measures.https://www.youtube.com/embed/ZzPgO5IwBk815602022-06-13T00:00:00+00:00yes https://riseof.ai/talks/our-ai-ambitions-for-germany-volker-wissing/https://i.ytimg.com/vi/9W-JnnG5qeo/hqdefault.jpgOur AI Ambitions for Germany – Volker Wissing (Rise of AI Conference 2024)At Rise of AI 2024, Dr. Volker Wissing, Germany's Federal Minister for Digital Affairs and Transport, outlines the federal government's AI agenda in a short video address. He opens on AI's double edge in cybersecurity, useful for detecting vulnerabilities and predicting attacks but also usable to generate new attack methods faster than before. He then turns to regulation, describing the EU AI Act, expected to enter into force in July 2024, as an innovation-friendly compromise he helped shape, to be implemented with the lightest possible touch through standards developed with the European Committee for Standardization and input from businesses. He stresses that AI governance is a global issue, citing a G7 code of conduct for advanced AI and Germany's continued engagement at the AI Seoul Summit. He presents Germany's Mission AI initiative, launched in 2023, including new regional AI hubs starting in Kaiserslautern and Berlin, new AI quality and test standards, and events connecting AI startups with small and medium-sized enterprises, summarizing the government's approach as education, intelligent regulation, promotion and inspiration.https://www.youtube.com/embed/9W-JnnG5qeo3602024-05-20T00:00:00+00:00yes https://riseof.ai/talks/overcoming-fundamental-problems-of-machine-intelligence-research-dagma/https://i.ytimg.com/vi/G8p9wc2RZVQ/hqdefault.jpgOvercoming Fundamental Problems of Machine Intelligence Research – Dagmar Monett (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Dagmar Monett, professor of computer science at the Berlin School of Economics and Law, presents research into why artificial intelligence still has no agreed definition and what her group is doing about it. Her team ran a survey, opened in July 2017 and still running at the time of the talk, that collected more than 550 responses from people in more than 57 countries and over 180 institutions, about 80% of them from academia; 82% of respondents said they work in AI. The survey asked whether existing definitions of AI are adequate, whether human and machine intelligence need separate definitions (80% said yes), and how respondents would define intelligence themselves, producing more than 4,000 free-text comments. Monett argues the field lacks consensus because it is more than 60 years old, interdisciplinary, contextual and a moving target, since capabilities once called intelligent later stop being seen that way. She presents quality criteria her team derived for good definitions, cognitive biases that distort discussion, and a catalog of properties meant to give researchers, regulators and companies a shared vocabulary for defining intelligent systems, a precondition, she argues, for workable AI regulation and ethics frameworks.https://www.youtube.com/embed/G8p9wc2RZVQ22202019-07-17T00:00:00+00:00yes https://riseof.ai/talks/panel-can-ai-heal-the-world-tanja-schindler/https://i.ytimg.com/vi/yQoOZ7uwmCk/hqdefault.jpgPanel: Can AI Heal the World? – Tanja Schindler, Daria Saharova, Janette Wiget, Mario Brandenburg (Rise of AI Conference 2022)At Rise of AI 2022 in Berlin, a panel moderated by futurist Tanja Schindler with Daria Saharova (World Fund), Janette Wiget (Merantix / AI Campus Berlin) and Mario Brandenburg (Parliamentary State Secretary, German Federal Ministry of Education and Research) discusses whether AI can solve major world problems. Saharova argues climate tech is where AI has the clearest positive impact, citing satellite-based crop and wildfire monitoring and new low-carbon materials such as cement alternatives; Wiget points to breast cancer screening AI and to her portfolio company Cambrium's protein-engineered materials replacing petrochemicals, and stresses that algorithms alone do not heal anything without usable products and cross-stakeholder collaboration; Brandenburg frames AI mainly as a tool for better, data-based political decision-making. The panel debates AI's own energy footprint, noting German data-center emissions reportedly exceed aviation's, and the tension between entrepreneurial curiosity and regulation. On risks, panelists argue technology is neutral and that visible bias in AI data is preferable to hidden bias, while agreeing Europe needs a common regulatory framework rather than each country acting alone. Audience questions cover European collaboration, encouraging corporate entrepreneurship, and public fear of AI, closing with a call to build trust through concrete products, not only ethics boards.https://www.youtube.com/embed/yQoOZ7uwmCk34202022-06-13T00:00:00+00:00yes https://riseof.ai/talks/panel-implications-of-artificial-intelligence-fabian-westerheide/https://i.ytimg.com/vi/mdiV5EWcmG0/hqdefault.jpgPanel: Implications of Artificial Intelligence – Fabian Westerheide, Jens Redmer, Trent McConaghy, Danko Nikolic, Achim Schlosser (Rise of AI Conference 2017)At Rise of AI 2017 in Berlin, a panel moderated by Fabian Westerheide with Jens Redmer (Google), Trent McConaghy, Danko Nikolic and Achim Schlosser (KPMG) debates whether AI is dangerous, whether it will destroy jobs, and how the resulting wealth should be distributed. The panel largely dismisses near-term superintelligence risk in favor of a nearer threat: process automation displacing a significant share of jobs within five years. Jens Redmer describes Google's open publication of research and its role in co-founding the Partnership on AI with Microsoft, Facebook, Apple and Amazon. Danko Nikolic argues a runaway intelligence explosion is impossible because intelligence can only develop through sustained interaction with the environment, though mundane AI systems accumulating resources uncontrollably still worry him. Trent McConaghy raises the danger of decentralized AI that cannot be shut down, then pivots to tokenized ecosystems such as Ethereum as a way to spread economic value to users rather than only founders and employees. The panel also discusses universal basic income, the useless class concept, positive medical and mobility use cases, and closes with audience questions on radical life extension, leaving Earth, and the simulation hypothesis.https://www.youtube.com/embed/mdiV5EWcmG034202017-05-25T00:00:00+00:00yes https://riseof.ai/talks/panel-scaling-ai-from-transformation-to-advantage-kenza-ait-si-abbou/https://i.ytimg.com/vi/Tw50O1IpwuU/hqdefault.jpgPanel: Scaling AI — From Transformation to Advantage – Kenza Ait Si Abbou, Claudia Pohlink, Ulli Waltinger (Rise of AI Conference 2026)At Rise of AI 2026 in Berlin, a panel with Kenza Ait Si Abbou (founder and CEO of scailers, former CTO and board member of FIEGE), Claudia Pohlink (Director of Data and AI at FIEGE) and Dr. Ulli Waltinger (Siemens), who also moderates, discusses what it takes to move enterprise AI from pilots to competitive advantage. Pohlink argues vibe coding is excellent for experimentation but a liability for ownership in regulated, industrial settings, and describes chatting with 15 years of her own downloaded LinkedIn data as the moment she understood AI's practical potential. Ait Si Abbou defines scaling as embedding AI in corporate strategy so it changes how a company makes money, not accumulating long lists of unimplemented use-case ideas, and stresses that architecture, data management, governance and culture must be in place first. Waltinger cites Siemens' internal "everyday AI" rollout, SiemensGPT, with more than 190,000 users. The panel debates Europe's AI sovereignty gap, weak marketing of European AI achievements such as Aleph Alpha and Black Forest Labs, agent governance, the shrinking role of the Chief Data Officer, and closes with bold 2030 predictions on digital twins, automated governance and voice interaction.https://www.youtube.com/embed/Tw50O1IpwuU28202026-07-15T00:00:00+00:00yes https://riseof.ai/talks/panel-the-singularity-might-be-closer-than-you-think-samim-winiger/https://i.ytimg.com/vi/dcjC-iwDNHs/hqdefault.jpgPanel: The Singularity Might Be Closer Than You Think – Samim Winiger, Ehssan Dariani, Ronnie Vuine, Danko Nikolic, Jan Klauck (Rise of AI Conference 2016)At Rise of AI 2016 in Berlin, a panel moderated by Samim Winiger with Ehssan Dariani, Ronnie Vuine, Danko Nikolic and Jan Klauck discusses whether the singularity is near. The panel first debates whether understanding intelligence is a precondition for building AGI, with one panelist arguing it is not, since humans do not fully understand their own brains either, and another distinguishing human-level from human-like intelligence. Asked to describe the world in 50 years, panelists offer visions ranging from smart robots doing unwanted work to humans merging with technology and uploading themselves. The discussion turns to whether the singularity movement already shapes policy, with panelists citing the NSA, homeopathy regulation and drug prohibition as examples of the gap between expert knowledge and political decisions. Panelists then name the technologies exciting them most, including high-resolution brain electrodes, cheap smartphones reaching poor populations, lab automation, and disappearing user interfaces. The panel closes on whether Moore's law's slowdown threatens the exponential case for the singularity.https://www.youtube.com/embed/dcjC-iwDNHs16802016-02-29T00:00:00+00:00yes https://riseof.ai/talks/path-to-singularity-how-authentic-are-thoughts-anish-mohammed/https://i.ytimg.com/vi/TgBtjI3KNa8/hqdefault.jpgPath to Singularity: How Authentic Are Thoughts? – Anish Mohammed (Rise of AI Conference 2016)At Rise of AI 2016 in Berlin, Anish Mohammed questions whether human thought is really 'authentic' compared to machine cognition, and traces a possible path toward brain-computer interfaces, whole-brain emulation and eventual superintelligence. He argues the human brain, using 8 to 20% of the body's energy, is already extended by devices like the iPhone, a primitive brain-computer interface limited by the bandwidth of eyes and fingers, and describes retinal implants as an early, already-existing way of feeding electronic signal directly into the optic nerve. He cites a science study showing human memories are unreliable yet highly valued as authentic, and argues privacy of thought has never been debated in EU policy the way data privacy has. Moving to governance, he uses the DAO hack as a cautionary example for any future system of emulated minds ('EMs'), and explains trusted platform modules and zero-knowledge proofs, specifically direct anonymous attestation, as tools that could let entities prove properties about themselves without revealing information. He closes on ethics for machines, the trolley problem for self-driving cars, and an extended audience Q&A.https://www.youtube.com/embed/TgBtjI3KNa821602016-08-25T00:00:00+00:00yes https://riseof.ai/talks/powering-change-in-ai-daniel-kiernan/https://i.ytimg.com/vi/NgBYTWWZ_pg/hqdefault.jpgPowering Change in AI – Daniel Kiernan (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, Daniel Kiernan, senior OEM alliances manager at NVIDIA, argues that the central challenge of AI is not a lack of data but the difficulty of turning that data into actionable insight. He walks through customer examples from healthcare, industry and customer service to show AI already at work rather than as a future technology. In healthcare, strokes kill more people worldwide than AIDS and tuberculosis combined, and Ohio State University has raised the efficiency of brain-scan diagnosis by 81 percent using an AI algorithm alongside its neurologists. In industry, GE uses sensor data and deep learning for predictive maintenance on machinery, saving more than six million dollars a year. Kiernan describes the end of Moore's Law and NVIDIA's GPU architecture, introduced around 2010, as the technology behind a predicted thousandfold performance increase by 2020, alongside rapid growth in developers and AI startups since 2013. He also explains NVIDIA's NVLink interconnect, co-developed with IBM for Power9 servers, and closes by inviting the audience to NVIDIA's GTC conference in Munich in October 2018.https://www.youtube.com/embed/NgBYTWWZ_pg12002018-06-10T00:00:00+00:00yes https://riseof.ai/talks/predicting-natural-disasters-testing-the-boundaries-of-computer-vision/https://i.ytimg.com/vi/y8P-AAAto6U/hqdefault.jpgPredicting Natural Disasters: Testing the Boundaries of Computer Vision – Sam Edds (Rise of AI Conference 2022)At Rise of AI 2022 in Berlin, Sam Edds, senior data scientist at Yelp and Z by HP Global Data Science Ambassador, presents a proof-of-concept project testing whether a computer vision model trained only on point-of-view photos of natural disasters can predict on aerial images it has never seen. Using a deep learning model trained on tweet-sourced point-of-view images of wildfire, flood and landslide incidents across categories like buildings, land, infrastructure and water, she evaluates it against a separate MIT lab dataset of low-altitude aerial disaster images. The point-of-view model predicts incidents almost perfectly and places correctly 9-90% of the time on its own data type. Applied out of sample to aerial images, it correctly identifies fire 85% of the time, flood 78%, and landslide 60%, while struggling badly with building types such as residential neighborhoods and house facades, since aerial views show little of the roof and facade detail visible from ground level. She argues the approach is promising for scaling low-cost, pre-trained tools to disaster response and hazard mitigation agencies, while stressing that biased input data always produces biased output regardless of the model used.https://www.youtube.com/embed/y8P-AAAto6U16802022-06-13T00:00:00+00:00yes https://riseof.ai/talks/quantifying-sustainability-of-an-ai-project-susan-wegner/https://i.ytimg.com/vi/2YUbvsRZ2zY/hqdefault.jpgQuantifying Sustainability of an AI Project – Susan Wegner (Rise of AI Conference 2023)At Rise of AI 2023 in Berlin, Susan Wegner, Managing Director at Deloitte Digital, presents an approach to measuring the ecological footprint of AI projects across their full lifecycle. She opens with a finding from MIT that digital solutions already produce more carbon emissions than aviation and cars, and cites studies showing GPT-3's training used energy equivalent to about 63 homes for a year, or 61 million phone charges, against roughly 3 homes and 3 million charges for the BLOOM model. She argues most attention goes to model training, while an 'iceberg' of other emissions, from employee devices and travel to data storage and ongoing monitoring, is usually ignored. Using a worked example from a small image-processing project with two employees, she shows how emissions accumulate across the lifecycle phases, with data processing and model development contributing the most. She reviews available measurement tools, including cloud-provider dashboards, a training footprint estimator and the open source tool CodeCarbon, and closes with practical levers for reducing emissions: model choice, hardware choice, cloud region and training timing.https://www.youtube.com/embed/2YUbvsRZ2zY18002023-05-14T00:00:00+00:00yes https://riseof.ai/talks/quantum-computing-and-ml-dream-team-or-just-the-next-hype-claudia-pohl/https://i.ytimg.com/vi/5ePQGiyJlPw/hqdefault.jpgQuantum Computing and ML: Dream Team or Just the Next Hype? – Claudia Pohlink (Rise of AI Summit 2020)At Rise of AI Summit 2020 in Berlin, Claudia Pohlink, Head of AI/ML at Telekom Innovation Laboratories, describes her team's two-year journey exploring quantum computing and quantum machine learning. She explains that qubits use superposition to hold multiple states at once and entanglement to let distant qubits interact instantly, which lets a quantum computer process combinations that grow exponentially with each added qubit. She focuses on optimization problems, illustrating the traveling-salesman-style routing problem with Deutsche Telekom's own network points, and describes the company's first real use case, frequency assignment planning for 2G mobile network towers, run on a quantum annealer and benchmarked against classical algorithms. She distinguishes gate computers such as IBM's and Google's from D-Wave's quantum simulator and Fujitsu's "quantum-inspired" digital annealing unit. In the Q&A, she says Deutsche Telekom has a ten-person team working on quantum topics, expects access to a real quantum computer next year, and describes convincing management to explore new technology before a business model exists as the hardest part of the work.https://www.youtube.com/embed/5ePQGiyJlPw18002020-11-30T00:00:00+00:00yes https://riseof.ai/talks/quantum-machine-learning-claudia-pohlink/https://i.ytimg.com/vi/Tjpn_VVqoLc/hqdefault.jpgQuantum Machine Learning – Claudia Pohlink (Rise of AI Virtual Chat 2020)At a Rise of AI Virtual Chat in 2020, host Fabian Westerheide talks with Claudia Pohlink of Deutsche Telekom's innovation labs about quantum machine learning. Pohlink, who leads the unit working on AI, blockchain and quantum computing at Telekom, explains her role as identifying trends and building a business around them rather than being a technical expert. She walks through the basics of qubits, superposition and entanglement, contrasts classical gate quantum computers such as IBM's with quantum-inspired hardware from Fujitsu and D-Wave, and argues the quantum business will be a cloud business. She cites Germany's roughly two-billion-euro investment in quantum hardware, Google's quantum-supremacy benchmark solving a task in 200 seconds versus 10,000 years for a classical supercomputer, and use cases in routing optimization, cryptography and quantum chemistry. Audience questions cover quantum entanglement, whether quantum machine learning deepens AI's black-box problem, and where to follow the field. Pohlink argues quantum computing may eventually help explain deep learning rather than obscure it further, while stressing that most current knowledge still comes from academic papers rather than mature products.https://www.youtube.com/embed/Tjpn_VVqoLc25202020-06-29T00:00:00+00:00yes https://riseof.ai/talks/race-to-ai-a-global-perspective-bj-rn-bringmann/https://i.ytimg.com/vi/MNt5X6YNipM/hqdefault.jpgRace to AI – A Global Perspective – Björn Bringmann (Rise of AI Conference 2022)At Rise of AI 2022 in Berlin, Björn Bringmann, partner and managing director of Deloitte's AI Institute, argues that the world is in a global AI race worth an estimated 12 trillion dollars a year, three times Germany's annual GDP, and that Europe still has a realistic chance to keep a seat at the table. He dates the modern race to 2015-2016, when AlphaGo's win over Lee Sedol triggered what he calls a Sputnik moment for China and prompted the Obama administration to accelerate AI policy. He contrasts three regional goals, US efficiency, Chinese social cohesion and European humanism, and shows the US far outspending Europe and China on R&D while China is closing the gap in both funding and startup activity. Drawing on a Deloitte survey of nearly 3,000 executives in 12 countries, he shows Germany and Europe lagging in turning AI investment into results compared with China. He closes by arguing Europe's biggest risk is not AI itself but the opportunity cost of inaction, and calls for more trust-building, a genuine EU digital single market, more public research funding, and a stronger pan-European innovation ecosystem.https://www.youtube.com/embed/MNt5X6YNipM18602022-06-13T00:00:00+00:00yes https://riseof.ai/talks/reading-the-signals-people-use-to-communicate-their-emotions-rana-gujr/https://i.ytimg.com/vi/jHoCfJlMHdM/hqdefault.jpgReading the Signals People Use to Communicate their Emotions – Rana Gujral (Rise of AI Conference 2023)At Rise of AI 2023, Rana Gujral, CEO of Behavioral Signals, argues that building systems closer to AGI requires modeling emotion and behavior, not just logic, since human decisions draw on both. He invokes Marvin Minsky's observation that the real question is not whether machines can have emotions but whether they can be intelligent without them, and argues a highly capable but emotionally blind system would function like a psychopath. Behavioral Signals measures emotion and behavior purely from non-verbal vocal cues, tone, pitch and prosody rather than words, producing classifiers for emotions, behaviors such as engagement or politeness, and industry-specific states like duress or coercion. Gujral describes a 'conversational bioprint' built from one to two minutes of audio and a case study at a European bank's debt-collection call center where matching agents to callers by bioprint improved loan-restructuring outcomes by 20 percent. He also describes a model predicting, with 80 to 83 percent accuracy, whether a debt holder will pay from the first 20 seconds of a call, while acknowledging sarcasm and data bias remain unresolved challenges.https://www.youtube.com/embed/jHoCfJlMHdM18602023-05-14T00:00:00+00:00yes https://riseof.ai/talks/ready-for-the-era-of-ai-irina-gontcharova/https://i.ytimg.com/vi/e-cZt5pGZDU/hqdefault.jpgReady for the Era of AI? – Irina Gontcharova (Rise of AI Conference 2024)At Rise of AI 2024 in Berlin, Irina Gontcharova, Director of Azure Infrastructure at Microsoft Deutschland, argues that AI does not solve human problems by itself but unleashes human creativity, much like the invention of the collapsible paint tube in 1841 freed painters to leave the studio and enabled impressionism. She traces how fast AI adoption is moving: ChatGPT reached mass adoption in about two months, far faster than mobile phones or the internet. She lays out what she calls the AI stack organizations need to get ready: infrastructure such as GPUs, a working data platform, application tooling built on top of models, and security and governance running through all of it. She stresses that Microsoft builds Copilot, not autopilot, keeping a human in the loop and in control. Using a live demo with an AI-generated balloon image, she shows how a model reasons about physics questions and where it still hedges or hallucinates. She closes by saying that readiness for AI requires imagination, which cannot come from a machine, combined with a responsible approach.https://www.youtube.com/embed/e-cZt5pGZDU15602024-05-21T00:00:00+00:00yes https://riseof.ai/talks/reduce-fear-of-ai-with-neuropsychology-katharina-von-knop/https://i.ytimg.com/vi/Eoobrw2Ug80/hqdefault.jpgReduce Fear of AI With Neuropsychology – Katharina von Knop (Rise of AI Conference 2023)At Rise of AI 2023 in Berlin, Dr. Katharina von Knop, founder and CEO of Digital Trust Analytics, argues that fear of AI is a neuropsychological problem that has to be addressed through interface and system design, not just messaging. She explains that in-person eye contact activates mirror neurons that build trust, which is why video calls feel exhausting, and that trust itself is fragile, energy-saving for the brain, and must be earned continuously. She describes how the amygdala reacts to unfamiliar or overly complex information, such as AI, with the same threat response triggered by seeing a spider, and how most human decisions are made unconsciously by the brainstem rather than the prefrontal cortex, with the conscious mind processing only a small fraction of available information. She presents a Maslow-style layered model of what trustworthy AI needs beyond factual problem-solving, including cybersecurity, transparency and accessibility, and criticizes GDPR consent notices, using Instagram's roughly 4,683-word declaration as an example of a legally compliant text designed in a way that discourages people from reading it. She closes with a Q&A on decision-making, cultural differences in fear, and why people fear rare risks like AI more than common ones like medical malpractice.https://www.youtube.com/embed/Eoobrw2Ug8020402023-05-14T00:00:00+00:00yes https://riseof.ai/talks/reflections-of-a-recovering-bio-narcissist-on-the-singularity-trent-mc/https://i.ytimg.com/vi/oPQ-bpMOip4/hqdefault.jpgReflections of a Recovering Bio-Narcissist on the Singularity – Trent McConaghy (Rise of AI Conference 2016)At Rise of AI 2016 in Berlin, Trent McConaghy argues that humans are already handing control of physical resources to narrow AI, through self-driving cars and trucks, deregulated electricity grids and other optimized systems, purely because it lowers cost. He describes how these separate optimized systems are being combined at higher levels and could merge with decentralized autonomous organizations (DAOs) to form self-owning, unstoppable AI DAOs. McConaghy lays out two scenarios for AI ending up with all human resources: humans voluntarily giving it away in the name of optimization, which he says is already happening, or a superintelligent AI "waking up" and taking it. He argues waking up is closer than expected because of Moore's Law, billions of advertising dollars flowing into AI research, maturing DAO infrastructure, and the absence of any fundamental cognitive trait that is uniquely human. His proposed defense is not regulation, which he considers wishful thinking, but for humans to increase their bandwidth to computers through brain-computer interfaces, gradually offloading computation onto silicon, or eventually uploading their brain dynamics entirely.https://www.youtube.com/embed/oPQ-bpMOip424602016-08-25T00:00:00+00:00yes https://riseof.ai/talks/responsible-ai-by-design-embedding-governance-into-systems-christian-g/https://i.ytimg.com/vi/sdfHqXIZpEc/hqdefault.jpgResponsible AI by Design: Embedding Governance into Systems – Christian Guttmann (Rise of AI Conference 2026)At Rise of AI 2026 in Berlin, on the Applied AI Stage, Christian Guttmann argues that the governance models most organizations use for AI were built for an older, predictive-AI paradigm and are now too slow for agentic systems that make decisions in real time. Drawing on work across telecom, finance, healthcare and software, he says the recurring failure modes he observes when AI adoption stalls have nothing to do with the technology itself: misaligned incentives, organizational silos, and threats to the identity of experts whose judgment AI could replace. He illustrates this with a hospital scheduling project in Australia that saved money but was blocked because the hospital's budget rules punished underspending, and a retail bank where product managers were paid to push individual products, undermining an AI built to recommend across the whole portfolio. His central proposal is to move governance out of monthly committee reviews and bolt-on policy documents and build it directly into the AI platform, through evaluation frameworks, gateways, agent identities and observability, so that velocity and trust grow together as systems move toward multi-agent and eventually embodied and reasoning-based AI.https://www.youtube.com/embed/sdfHqXIZpEc19202026-07-15T00:00:00+00:00yes https://riseof.ai/talks/responsible-ai-for-carbon-neutrality-leif-nissen-lundb-k/https://i.ytimg.com/vi/SWvP5zmANrU/hqdefault.jpgResponsible AI for carbon neutrality – Leif-Nissen Lundbæk, Andreas Grün (Rise of AI Conference 2023)At Rise of AI 2023 in Berlin, Andreas Grün, head of technology for ZDF's digital media, and Leif-Nissen Lundbæk, co-founder and CEO of Xayn, describe building energy-efficient, privacy-preserving recommendation systems for German public broadcaster ZDF's streaming platform Mediathek. Grün explains that roughly 50% of Mediathek's viewing volume comes from algorithmically generated recommendations, built by a personalization team ZDF formed in 2018, and that ZDF developed its own 'PSM metrics' (covering coverage, novelty, diversity and serendipity) and a public transparency site to bridge public-service-media values with data-science metrics, plus a debiasing method that increased overall viewing while surfacing less popular content. Lundbæk describes Xayn's approach of small, specialized language models rather than large general ones, citing a joint test where a zero-shot model matched ZDF's custom-trained recommender's click rate while using 98% less energy, computable on a mobile phone instead of a data center. Both argue Europe's stricter data constraints can drive more efficient, more carefully engineered AI rather than only limiting it.https://www.youtube.com/embed/SWvP5zmANrU16802023-05-14T00:00:00+00:00yes https://riseof.ai/talks/responsible-ai-use-by-law-enforcement-risks-and-benefits-irakli-beridz/https://i.ytimg.com/vi/cfQW2bfEX4g/hqdefault.jpgResponsible AI Use by Law Enforcement: Risks and Benefits – Irakli Beridze (Rise of AI Conference 2024)At Rise of AI 2024, Dr. Irakli Beridze, head of the Centre for Artificial Intelligence and Robotics at UNICRI, a United Nations agency, argues that governing AI is one of the major challenges of the current era, using law enforcement as the sharpest test case. He traces how, after organizing the UN's first AI meeting in 2015, when many delegations dismissed the topic as science fiction, AI governance became a UN priority, especially once Secretary-General António Guterres called AI a "game changer" in 2017. He describes UNICRI's work with INTERPOL since 2017 on a governance instrument for law enforcement, motivated partly by the sheer scale of data agencies must analyze, and highlights the AI for Safer Children program, which helps identify and rescue victims of sexual abuse. He then presents UNICRI's seven-part AI toolkit for responsible use of AI by law enforcement, developed over three years with EU funding, unveiled in Singapore in 2023, and tested in 15 countries, closing with next steps at the UN level, including a governance blueprint from the Secretary-General's Advisory Board.https://www.youtube.com/embed/cfQW2bfEX4g15002024-05-20T00:00:00+00:00yes https://riseof.ai/talks/rising-against-the-giants-state-of-llms-foundation-models-in-europe-va/https://i.ytimg.com/vi/e8L2S4vcNOk/hqdefault.jpgRising Against the Giants: State of LLMs/Foundation Models in Europe – Vanessa Cann, Peter Sarlin, Larissa Holzki, Nicolas Flores-Herr (Rise of AI Conference 2024)At Rise of AI 2024 in Berlin, a panel moderated by Larissa Holzki (Handelsblatt) with Vanessa Cann (KI Bundesverband), Peter Sarlin (CEO and co-founder, Silo AI) and Nicolas Flores-Herr (Fraunhofer IAIS) discusses whether Europe can build competitive large language models against OpenAI and Microsoft. The panelists agree OpenAI dominates industry and political mindshare with Microsoft's backing, but argue the best model is not necessarily the biggest, and that Europe should focus on smaller, specialized, multilingual and industrial models rather than a general-purpose chatbot. Sarlin presents Silo AI's newly released Viking model for Nordic languages, arguing GPT-4 speaks Finnish or Swedish like a translated American model. Flores-Herr describes Fraunhofer's openGPT-X project and a new EuroHPC-funded initiative training models in 45 languages. Cann warns Europe risks becoming merely a deployment market for US models unless companies rethink their business models, not just bolt AI onto existing products, and shares experience collaborating with a Shanghai AI team. The panel closes on cautious hope, tempered by fear that Microsoft becomes Europe's default answer.https://www.youtube.com/embed/e8L2S4vcNOk25802024-05-20T00:00:00+00:00yes https://riseof.ai/talks/roadmapping-a-successful-ai-journey-from-grassroots-to-board-rooms-chr/https://i.ytimg.com/vi/vw4TtwwY0ig/hqdefault.jpgRoadmapping a Successful AI Journey: From Grassroots to Board Rooms – Christian Guttmann (Rise of AI Summit 2020)At the Rise of AI Summit 2020, Christian Guttmann, Chief AI Officer at TietoEVRY, draws on almost 20 years working with businesses across four continents to outline what boardrooms and grassroots employees each need for AI adoption to succeed. Structured around eight reflections, or 'ducks,' he argues boards need entrepreneurial, technically literate members, CEOs must personally learn the technology rather than delegate it, and organizations must build trust with employees by framing AI as augmenting tasks rather than replacing jobs. He challenges the assumption that AI always requires massive legacy data, citing the second version of AlphaGo, which learned purely from the rules of the game, and describes a 'second wave' of AI maturity in which purely technical data-science teams gain business, change-management and organizational mandate. Guttmann discusses the scarcity of top AI talent, estimated at roughly 10,000 people worldwide, the risks of choosing the wrong technology partner, and why so many proof-of-concept projects end up in what he calls the 'POC graveyard' instead of scaling into full production.https://www.youtube.com/embed/vw4TtwwY0ig23402020-11-30T00:00:00+00:00yes https://riseof.ai/talks/scaling-ai-for-industry-feiyu-xu/https://i.ytimg.com/vi/uDasoYzizmg/hqdefault.jpgScaling AI for Industry – Feiyu Xu (Rise of AI Conference 2025)At Rise of AI 2025 in Berlin, Feiyu Xu, Professor of Industry AI, opens the Applied AI Stage by arguing that scaling AI in industry depends on ecosystems, governance and a clear strategy rather than on model quality alone. She points to Llama 4 Scout, which runs on a single H100 GPU with a context window of almost 10 million tokens, as a step toward industrial adoption, and urges every company to define an "AI north star" that turns hundreds of scattered use cases into a roadmap, using autonomous driving for carmakers and passenger experience for airports as examples. She stresses that companies need a full data inventory, an application stack they control themselves, and a central AI team responsible for strategy, the development stack, and scalable delivery. Her longtime collaborator Patrick Monk then presents agentic AI for enterprise workflows, demonstrating an email-triggered ordering agent and comparing model accuracy on business-process automation, from GPT-4o to DeepSeek R1 and OpenAI's o4-mini.https://www.youtube.com/embed/uDasoYzizmg18602025-05-21T00:00:00+00:00yes https://riseof.ai/talks/scaling-ai-creating-value-with-the-application-of-ai-andreas-liebl/https://i.ytimg.com/vi/d3joovS54lI/hqdefault.jpgScaling AI: Creating Value with the Application of AI – Andreas Liebl (Rise of AI Summit 2020)At the Rise of AI Summit 2020 in Berlin, Andreas Liebl, Managing Director of UnternehmerTUM and the appliedAI Initiative, presents a maturity model for how companies scale artificial intelligence and explains why most struggle to get value from it. He cites an MIT and BCG study finding that 90% of companies have invested in AI but only 40% report any business gains. Liebl argues the core difficulty is that AI differs structurally from traditional software: it depends on data rather than code, on training rather than development, and on ongoing evaluation rather than one-time verification. He walks through appliedAI's four-stage maturity model, from experimenter through practitioner, professional, to shaper, and uses a computer-vision quality-control example to show how requirements change as a single use case scales into an enterprise-wide, board-level topic. He presents appliedAI's newly published AI Journey Map, a tool for structuring the challenges companies face at each stage, and argues that scaling AI ultimately depends less on technology than on organizational ambition and board-level commitment.https://www.youtube.com/embed/d3joovS54lI17402020-11-30T00:00:00+00:00yes https://riseof.ai/talks/scaling-nlp-to-the-world-s-languages-sebastian-ruder/https://i.ytimg.com/vi/rpM-3gvkWQg/hqdefault.jpgScaling NLP to the World’s Languages – Sebastian Ruder (Rise of AI Conference 2022)At Rise of AI 2022 in Berlin, Sebastian Ruder, a senior research scientist at Google working on language processing and deep learning, argues that current NLP systems and large language models remain accessible mainly to English and a few well-resourced languages, leaving roughly 3 billion speakers of the next 1,000 languages underserved. He shows that multilingual model benchmarks look promising only because they average over the few languages that datasets actually cover, while most languages remain untested. Ruder outlines four directions needed to close this gap: computationally and data-efficient models that use inductive biases and adapter layers rather than ever-larger parameter counts; multi-modal models that draw on speech, radio and video since most of these languages have little text or web presence; evaluation on real-world data instead of translated datasets, which carry translation artifacts and the biases of the original English data creators; and treating languages as a continuum of varieties and dialects rather than fixed monoliths. He closes by describing the need to build data resources together with local speaker communities rather than through centralized annotation alone.https://www.youtube.com/embed/rpM-3gvkWQg18602022-06-13T00:00:00+00:00yes https://riseof.ai/talks/scaling-sovereign-ai-in-banking-julia-koch/https://i.ytimg.com/vi/ZFhx3iftCLc/hqdefault.jpgScaling Sovereign AI in Banking – Julia Koch (Rise of AI Conference 2026)At Rise of AI 2026 in Berlin, Julia Koch, managing director at Finanz Informatik, the central IT partner of the German Savings Bank Group (Sparkasse), explains how her organization is scaling sovereign AI from assistance tools to agentic systems across more than 350 independent legal entities and about 200,000 employees. Finanz Informatik runs its own data centers, built before ChatGPT existed, and operates an on-premise AI platform using open-source models where possible to avoid vendor lock-in, developed with engineering support from Nvidia. Its flagship tool, the SKI-Pilot (SAI-Pilot), is used by 200,000 employees, generated 2.8 million prompts in a recent ten-day period, and its meeting-preparation agent cut advisor prep time from 30-45 minutes to seconds, with over 175,000 meeting preparations completed in April. Koch describes deep integration with core banking systems and Outlook as key adoption drivers, and previews a widget-based, role-specific dashboard planned for deployment in June to support further agentic capabilities in a highly regulated environment.https://www.youtube.com/embed/ZFhx3iftCLc18602026-07-15T00:00:00+00:00yes https://riseof.ai/talks/science-transfer-and-ai-tina-kl-wer/https://i.ytimg.com/vi/15MDOVpK4T0/hqdefault.jpgScience Transfer and AI – Tina Klüwer (Rise of AI Conference 2024)At Rise of AI 2024 in Berlin, Tina Klüwer, five months into her role at the German Federal Ministry of Research and Education (BMBF), explains how Germany turns AI research into industry applications. She traces the government's AI strategy from its 2018 launch, one of the first national AI strategies worldwide, through its 2020 update into six pillars including talents, research, transfer and applications, world of work, frameworks and standards, and society, backed by a total budget of 3.5 billion euros. She shows that Germany has a strong research base, including over 90 AI research institutions, the 1988-founded DFKI, and the 1997 LSTM breakthrough by Hochreiter and Schmidhuber, but ranks only 18th of 27 EU states at turning that research into applications. She presents the Ministry's Action Plan AI, published November 2023, with concrete transfer measures: SME funding, regional AI service centers, expanded GPU computing access, and talent programs including new AI professorships and the AI Campus platform.https://www.youtube.com/embed/15MDOVpK4T011402024-05-21T00:00:00+00:00yes https://riseof.ai/talks/science-will-eat-its-children-georg-wittenburg/https://i.ytimg.com/vi/39x3l0mVOh8/hqdefault.jpgScience Will Eat Its Children – Georg Wittenburg (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Georg Wittenburg, co-founder and CEO of Inspirient, argues that AI is redefining which data science tasks are hard, by automating large parts of the discipline itself. He describes building, over about four years, 226 classifiers that automate steps from file-format detection through data cleaning, time series analysis and pattern or outlier detection, and says one such automatically generated result was presented to a company board for the first time in September of the prior year. He uses a Deutsche Bahn workshop and an insurance company case to show how automated results change the conversation between data scientists and business stakeholders, and uses the US EPA vehicle emissions dataset to demonstrate how automation surfaces findings analysts would not have thought to search for, illustrating the "streetlight effect" in data analysis. He closes with real client findings, from fraud detection to misidentified target audiences, and in the Q&A predicts the population of data scientists will keep growing even as automation shifts their work toward communicating results rather than producing them.https://www.youtube.com/embed/39x3l0mVOh815002019-07-15T00:00:00+00:00yes https://riseof.ai/talks/shaping-the-future-unleashing-the-potential-for-ai-startups-worldwide/https://i.ytimg.com/vi/l7lwij_KxUI/hqdefault.jpgShaping the Future: Unleashing the Potential for AI Startups Worldwide – Sabine Wiesmüller (Rise of AI Conference 2024)At Rise of AI 2024 in Berlin, Sabine Wiesmüller, Director of the AI Competence Center at Start2 Group, argues that European AI startups need to define global niches and expand into other regions rather than trying to mimic the United States. She outlines Europe's structural weaknesses: relatively low global AI market share, weak research-to-application transfer, startups that stay too small for one region, roughly 75% of European exits going to non-European buyers, and a persistent gap in late-stage investment. She then takes the audience through opportunity hubs around the world, including Boston and Sao Paulo in the Americas, Singapore, Beijing and Bangalore in Asia, and manufacturing and fintech growth in Chile and Brazil, citing statistics on elite AI talent shifting from the US toward India and China between 2019 and roughly 2022. She closes with market trends such as agentic AI, specialized large language model applications, and AI-driven drug discovery, and advises startups and corporates to treat ecosystems, regulatory differences and AI adoption strategically rather than defensively.https://www.youtube.com/embed/l7lwij_KxUI14402024-05-21T00:00:00+00:00yes https://riseof.ai/talks/solving-the-world-s-greatest-challenges-jaap-zuiderveld/https://i.ytimg.com/vi/8YVpr2TFvjg/hqdefault.jpgSolving the World’s Greatest Challenges – Jaap Zuiderveld (Rise of AI Conference 2022)At Rise of AI 2022 in Berlin, on the Applied AI Stage, Jaap Zuiderveld of NVIDIA argues that NVIDIA is best understood as a software company rather than a hardware maker: of its 24,000 employees, 22,000 work in engineering and 70 percent of those do software. He walks through NVIDIA's stack of pretrained models and SDKs, including Modulus, Clara, Riva, Maxine, Merlin, Omniverse Avatar, Drive, Isaac, Metropolis and Holoscan, and gives customer examples for each, from Siemens Energy's wind turbines to Amex's call-center voice recognition. He stresses that acceleration matters because waiting for results wastes the time of expensive data scientists, and cites growth figures: 3 million developers, more than 1,300 partners, 25,000 customers and 2,700 accelerated ISV applications. He highlights partnerships with Daimler on self-driving software and with BMW on an Omniverse digital twin of its factories, and describes AstraZeneca's use of an NVIDIA supercomputer to speed up COVID vaccine development. He closes by describing simulating the physical world in virtual environments as NVIDIA's next major wave.https://www.youtube.com/embed/8YVpr2TFvjg16802022-06-13T00:00:00+00:00yes https://riseof.ai/talks/state-of-ai-2025-fabian-westerheide/https://i.ytimg.com/vi/H5hbLbi8WE4/hqdefault.jpgState of AI 2025 – Fabian Westerheide (Rise of AI Conference 2025)At Rise of AI 2025 in Berlin, in his opening keynote "State of AI 2025," Fabian Westerheide, CEO of Rise of AI and AI.Fund, surveys the global AI landscape under the year's theme "Good News from Europe." He argues China has proven itself the clear technological number two, pointing to DeepSeek and Manus as evidence it can take American innovation and make it leaner and more cost-efficient, while the United States remains number one and is now largely unleashed from regulatory constraints as government and tech industry interests align. He notes new investment hubs emerging in Saudi Arabia and the UAE, including a deal in which Saudi Arabia is pushed to invest a reported one trillion dollars in exchange for one hundred billion back. He argues Europe cannot compete with the US and China on large language models given its gaps in talent, resources, capital and infrastructure, and must instead become smaller, slower and more specialized, building on many small success stories rather than one big win. He then walks the audience through the day's three stages, Policy & Society, Applied AI and a new offline "Cognitive Labs" format, and their speakers.https://www.youtube.com/embed/H5hbLbi8WE410202025-05-21T00:00:00+00:00yes https://riseof.ai/talks/status-quo-in-politics-and-society-and-why-ai-could-be-the-game-change/https://i.ytimg.com/vi/foSMuG3PnvY/hqdefault.jpgStatus Quo in Politics and Society, and Why AI Could Be the Game Changer – Mario Brandenburg (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Mario Brandenburg, a member of the German Bundestag, describes moving from the IT world into federal politics and finding himself acting as a translator between people in tech, ordinary citizens, and career politicians who, in his view, do not understand technology. He argues that digital politics differs fundamentally from classical industry politics: a state could once simply refuse to build a bridge or road, but it cannot stop technologies like Airbnb or Uber once people demand them, which makes speed the only currency that matters. He proposes three areas for speeding up Germany's AI adoption: building an ecosystem (English as a second administrative language, keeping the country decentralized), unlocking finance (state capital and pension reserves invested in founders rather than bonds, connecting startups, established firms and wealthy family offices), and political commitment (loosening restrictive data rules and telling a positive, visionary story about technology). He closes urging the mostly non-political audience to get politically active.https://www.youtube.com/embed/foSMuG3PnvY6002019-07-01T00:00:00+00:00yes https://riseof.ai/talks/superintelligence-hans-uszkoreit/https://i.ytimg.com/vi/rHMBMlzG2XQ/hqdefault.jpgSuperintelligence – Hans Uszkoreit (Rise of AI Conference 2017)At Rise of AI 2017 in Berlin, Hans Uszkoreit, Scientific Director at the German Research Center for Artificial Intelligence, asks not how to build superintelligence but whether it can exist at all, and if so, where. He argues AI already shows superhuman performance in narrow tasks, citing Deep Blue at chess, IBM Watson at Jeopardy, AlphaGo, and self-driving cars, but distinguishes this from genuine intelligence. He breaks human cognition into innate instincts, acquired explicit knowledge such as facts and symbolic sequences, and acquired implicit knowledge such as language and procedural skills, then maps these onto two separate families of AI systems: symbolic, knowledge-based systems and statistical, learned-behavior systems such as neural networks. He argues these two families are not yet combined: neural networks such as machine translation systems produce results without understanding, lack reusable knowledge, and cannot explain their own decisions. Uszkoreit predicts that combining learned behavior with large, growing knowledge graphs, rather than any single self-conscious system, will drive the next leap in AI capability, and rejects Hollywood scenarios of an uncontrollable evil AI, while expecting eventual benefits including augmented human cognition and longer, safer lives.https://www.youtube.com/embed/rHMBMlzG2XQ18602017-05-25T00:00:00+00:00yes https://riseof.ai/talks/supporting-the-ai-journey-through-2030-edmondo-orlotti/https://i.ytimg.com/vi/A17uqUNwyjs/hqdefault.jpgSupporting the AI Journey through 2030 – Edmondo Orlotti (Rise of AI Conference 2022)At Rise of AI 2022 in Berlin, Edmondo Orlotti, AI business development lead at Hewlett Packard Enterprise and a former Nvidia employee, argues that scaling AI into production is mostly a data and infrastructure problem, not a modeling problem. Citing an Ericsson Mobility Report forecast of 370 exabytes of data generated per month on wireless networks by 2027, he argues data volume is becoming unmanageable and that a cloud-only strategy cannot work, pushing HPE toward an edge-to-cloud approach. He illustrates this with HPE's partnership with the Mercedes Formula One team and an end-to-end platform built for Volvo Cars, through its subsidiary Zenseact, to collect, store and process the hundreds of petabytes of data needed to validate autonomous driving software. He describes tools HPE has built for production AI, including Determined AI for training large models at scale, swarm learning for training on sensitive data without moving it, and an MLOps platform for managing model life cycles, plus SmartSim, from its Cray acquisition, for embedding AI into traditional simulation. He closes by naming large language models and the metaverse as the trends he expects to most affect daily life.https://www.youtube.com/embed/A17uqUNwyjs17402022-06-13T00:00:00+00:00yes https://riseof.ai/talks/symphonia-universalis-su-a-journey-into-sound-marc-engenhart/https://i.ytimg.com/vi/BfIt2Jvkl_E/hqdefault.jpgSymphonia Universalis (#SU): a journey into sound – Marc Engenhart (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Marc Engenhart, head of design studio Engenhart, presents Symphonia Universalis (#SU), a man-machine art installation his six-to-eight-person team has spent nearly a year building for the Beethoven anniversary in Bonn in 2020. He traces the idea to visiting Beethoven's birthplace and reading Beethoven's character as visionary, humanist and boundary-expanding, which he treats as a template for an artificial persona. To build it, his team digitized Beethoven's full catalogue (Opus 1 through 138 plus roughly 90 unlabeled works) into MIDI data, engineered features describing his persona from letters and research, consulted a criminal profiler to draft a psychological profile translated into algorithms, modeled mood and crisis states such as his breakup, and fed all of it into a recurrent neural network alongside live human input he calls a "heartbeat." The result, installed as a black cube people can visit, touch and feel vibrate, continuously composes new music from public contributions worldwide, intended to run without updates or a defined end date.https://www.youtube.com/embed/BfIt2Jvkl_E16802019-07-17T00:00:00+00:00yes https://riseof.ai/talks/talk-at-rise-of-ai-2016-jan-klauck/https://i.ytimg.com/vi/uC757D2Gkno/hqdefault.jpgTalk at Rise of AI 2016 – Jan Klauck (Rise of AI Conference 2016)At Rise of AI 2016 in Berlin, an event hosted by Fabian Westerheide for 100 selected guests including scientists, investors, journalists, corporates, entrepreneurs and thinkers, Jan Klauck speaks on integrating advanced artificial intelligence into society. According to the event description, the evening's overall theme was "The Singularity might be closer than you think," and Klauck's talk summarizes the status of AI at the time and the outlook for artificial machine intelligence in the coming years. No usable transcript is available for this recording because speech recognition failed, so the specific arguments, examples and figures Klauck presented cannot be reconstructed here. This page is therefore limited to what the event description states about the talk's topic and framing, without inferring additional content, claims or numbers that are not explicitly given in the available material.https://www.youtube.com/embed/uC757D2Gkno10802016-02-28T00:00:00+00:00yes https://riseof.ai/talks/technology-education-an-emerging-transdiscipline-hans-uszkoreit/https://i.ytimg.com/vi/3Ufm6YWO7fU/hqdefault.jpgTechnology Education: An Emerging Transdiscipline – Hans Uszkoreit (Rise of AI Conference 2024)At Rise of AI 2024, Hans Uszkoreit argues that the real bottleneck in today's foundation models is not algorithms, architectures or compute, but how the models are trained, or in his words, 'educated'. He observes that European language models are not on top of leaderboards despite Europe building smaller, industry-focused systems, and traces this to gaps in training data rather than weaker methods, noting that all major jumps since 2022, from GPT to Llama, use versions of the same Transformer architecture and differ mainly in the data that went into them. Drawing on his own testing, he shows that pretraining data collected opportunistically from sources like Common Crawl covers some domains, such as medicine and law, far better than others, including most industrial and manufacturing knowledge, and that this data gap explains phenomena such as hallucination and inconsistency across languages. He argues models trained this way perform at roughly bachelor's-textbook level in specialized industrial domains, and calls for a new transdiscipline, merging education science, information science, AI and educational psychology, to identify what knowledge is missing, source data for it, and systematically teach and test models the way people are educated.https://www.youtube.com/embed/3Ufm6YWO7fU15002024-05-20T00:00:00+00:00yes https://riseof.ai/talks/the-age-of-ai-in-2030-daniel-jeffries/https://i.ytimg.com/vi/q_KPNtmc9m8/hqdefault.jpgThe Age of AI in 2030 – Daniel Jeffries (Rise of AI Summit 2020)At Rise of AI Summit 2020 in Berlin, Daniel Jeffries, Chief Technical Evangelist at Pachyderm, says he wants to focus only on the positive changes AI will bring in the next decade, after previously covering 5, 50 and 500-year horizons. He argues intelligence has driven every past leap in human history, from the agricultural revolution to the information age, and that AI needs a shared, Linux-like infrastructure stack before it can spread beyond big tech, an effort he connects to his own work with a 15-company Artificial Intelligence Infrastructure Alliance. He predicts AI will transform the arts, citing OpenAI's Jukebox recreating voices like Frank Sinatra, and will cut blockbuster film costs by blending digital and real actors. In healthcare, he traces rapid gains in disease detection, from Google's skin cancer algorithm reaching 76 percent accuracy in 2017 to 96 percent by 2019, and a Google research team's 99 percent accurate breast cancer detector called LYNA. He also describes an Oak Ridge supercomputer analysis that reframed COVID-19 as a vascular disease via the "bradykinin hypothesis" and identified nine existing drugs with possible efficacy.https://www.youtube.com/embed/q_KPNtmc9m818602020-11-20T00:00:00+00:00yes https://riseof.ai/talks/the-ai-commons-trent-mcconaghy/https://i.ytimg.com/vi/5cYFLZ9QNo4/hqdefault.jpgThe AI Commons – Trent McConaghy (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Trent McConaghy, founder of Ocean Protocol, argues that AI can be aimed at the UN's 17 Sustainable Development Goals, which he calls a de facto KPI for humanity, but that scattered AI-for-good projects will not reach global scale without better infrastructure connecting problem owners to problem solvers. He proposes an 'AI Commons': a public utility network, built on blockchain technology, that connects data owners, storage and compute providers and AI researchers the way ImageNet or the UCI repository connected researchers to well-defined problems. Using Bitcoin as an example of a public network no one owns or controls, he describes using token inflation to pay suppliers, such as telecom companies, for data like cell-tower signal changes useful for weather prediction, so that data stays free for users while suppliers are still compensated. He also describes fully decentralized federated learning, where hospitals train shared models without a central party controlling the data or the result, as a way to pool medical data such as DNA samples for cancer research without violating privacy. He cites pilot projects with hospitals in Munich and Singapore and a Grow Asia project on fertilizer allocation for farmers.https://www.youtube.com/embed/5cYFLZ9QNo412602019-07-18T00:00:00+00:00yes https://riseof.ai/talks/the-ai-tipping-point-gilles-backhus/https://i.ytimg.com/vi/jrGBUnlM7iQ/hqdefault.jpgThe AI Tipping Point – Gilles Backhus (Rise of AI Conference 2025)At Rise of AI 2025 in Berlin, Gilles Backhus, Head of AI at Recogni, argues that AI adoption is approaching a tipping point defined by cost and speed rather than raw capability. Recogni builds AI chips and data-center systems, which gives the company a bottom-up view of what AI actually costs. Backhus explains that global AI compute is shifting from training to inference, projected to reach 95-99% inference by 2030, and that inference costs for advanced multi-model agent stacks have risen roughly 100x per million tokens because accuracy compounds negatively across chained models. He walks through enterprise dilemmas around where to integrate AI, what it costs, and how to manage internal and external change, citing Shopify and Klarna's hiring reversals as examples of unstable dynamics. He introduces real-time GenAI, especially real-time video generation, as the next unlock, using a hypothetical $18 trillion AI-education market to illustrate current costs of roughly $100 per hour of AI video. He closes by describing Recogni's approach to cutting cost 10-100x through logarithmic math, faster chip-to-chip networking, and purpose-built systems.https://www.youtube.com/embed/jrGBUnlM7iQ16802025-05-21T00:00:00+00:00yes https://riseof.ai/talks/the-berlin-ai-ecosystem-charlotte-seiler/https://i.ytimg.com/vi/OObU32byyGA/hqdefault.jpgThe Berlin AI Ecosystem – Charlotte Seiler (Rise of AI Summit 2020)At the Rise of AI Summit 2020, Charlotte Seiler, AI Innovation Manager at Berlin Partner, the city's local economic development agency, gives an overview of Berlin's AI ecosystem. She reports more than 220 AI companies in the Berlin-Brandenburg region, close to 30 percent of all German AI companies, drawing on research institutions such as the Technical University, the newly formed BIFOLD AI learning center, Fraunhofer, DFKI, and Charite for health-related AI. Business intelligence and process management account for 36 percent of local AI applications, health about 10 percent, followed by mobility, commerce, entertainment and robotics. She highlights major corporate AI labs, including Amazon's, alongside scale-ups like Merantix and startups such as ADA Health, and describes community infrastructure like the AI Monday meetup series she co-organizes, the Berlin AI website, and the upcoming Merantix AI Campus. Seiler's stated goal is to bundle Berlin's AI activities under one overarching initiative and website so the ecosystem can speak with one voice internationally, while continuing to attract talent and shape enabling regulation.https://www.youtube.com/embed/OObU32byyGA10202020-11-23T00:00:00+00:00yes https://riseof.ai/talks/the-democratization-of-ai-dinakar-munagala/https://i.ytimg.com/vi/dIBzzs8efyg/hqdefault.jpgThe Democratization of AI – Dinakar Munagala (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Dinakar Munagala, co-founder and CEO of Thinci, argues that four barriers are slowing AI adoption: cost, talent, time and data, and describes how new processor architectures and tooling could lower them and bring AI to the masses, much as cheap computing, operating systems and the internet drove the PC revolution and touch UIs and app stores drove the mobile revolution. He says building an AI application today needs cloud compute that gets expensive over months of training, or hardware costing up to 300,000 dollars, plus a large team of data engineers, data scientists and ML engineers, with 50 to 60 percent of time spent just collecting and cleaning data. He points to a global shortage of AI talent, citing a figure of about 300,000 AI researchers and practitioners worldwide against a McKinsey estimate of a quarter-million-person US data scientist shortfall by 2020. Munagala describes Thinci's programmable graph processor architecture, built to accelerate AI workloads more efficiently than CPUs or GPUs, and points to low-code tools, transfer learning, model marketplaces and synthetic datasets as ways to let non-experts, or "citizen data scientists," build AI applications.https://www.youtube.com/embed/dIBzzs8efyg14402019-07-17T00:00:00+00:00yes https://riseof.ai/talks/the-democratization-of-technology-a-world-where-anyone-can-use-a-robot/https://i.ytimg.com/vi/KXuFsgoxiD8/hqdefault.jpgThe Democratization of Technology: A World Where Anyone Can Use a Robot – Simon Haddadin (Rise of AI Summit 2020)At the Rise of AI Summit 2020, Simon Haddadin, CEO and co-founder of Franka Emika, presents his company's vision of robotics as a tool for everyone, comparable to how personal computers democratized computing. Speaking remotely due to COVID-19 from Franka Emika's Munich lab, he argues that robots today remain too expensive, inflexible and confined behind safety fences to perform tasks like assembly, grasping or testing, which is why almost no 3C manufacturing (computers, communication devices, consumer electronics) remains in Europe. He contrasts digital AI milestones such as Deep Blue and DeepMind's AlphaGo with the unsolved challenge of transferring intelligence into physical manipulation, illustrated by the DARPA Robotics Challenge. Through a live lab demonstration, he shows Franka Emika's robot learning tasks by human demonstration, learning insertion strategies itself through force and motion data, and building its own task sequence without being told which apps to use. He argues robots are essential during the pandemic for manufacturing, healthcare and elderly care, and closes by positioning Europe as a leader in mechatronic and cyber-physical systems even where it lags in AI compute.https://www.youtube.com/embed/KXuFsgoxiD821602020-11-30T00:00:00+00:00yes https://riseof.ai/talks/the-dirty-secrets-of-ai-michael-maria-bommer/https://i.ytimg.com/vi/LRs6M6BqaPA/hqdefault.jpgThe Dirty Secrets of AI – Michael Maria Bommer (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, Michael Maria Bommer, SVP EMEA at LivePerson, presents a talk titled 'The dirty secrets of AI'. Speech recognition for this recording failed, so no transcript is available, and the YouTube description gives only the speaker's name, his role at LivePerson, and the talk title itself, without describing the talk's arguments, examples or claims. Because the title promises a critical look at overlooked problems within artificial intelligence, it can be assumed the talk challenges some conventional narrative about AI, but the specific issues referenced as 'dirty secrets' cannot be confirmed from the material available for this page. No topics, numbers, case studies or quotations from the talk itself could be extracted. Readers seeking the actual content of this 20-minute talk should watch the original recording, since this page is built entirely from metadata rather than from the spoken content.https://www.youtube.com/embed/LRs6M6BqaPA12002018-06-10T00:00:00+00:00yes https://riseof.ai/talks/the-eu-ai-act-the-good-the-bad-and-a-tiny-bit-of-hope-felix-bro-mann/https://i.ytimg.com/vi/aiccyX_ezYs/hqdefault.jpgThe EU AI Act: The Good, the Bad, and a Tiny Bit of Hope – Felix Broßmann (Rise of AI Conference 2024)At Rise of AI 2024 in Berlin, Felix Broßmann, a partner at SKAD AG, gives an overview of the EU AI Act based on his firm's consulting work in AI governance for banks, insurers and startups. He opens by arguing that regulation is needed because generative AI carries real, demonstrated risks: answer quality degrading over time, training data being extractable from models, backdoors surviving safety training, bias in outputs, and chatbots that can be manipulated into damaging statements, such as a car dealership bot offering a car for one dollar or a jailbreak that bypasses safety filters by asking in Zulu. He then explains the Act's risk-based, four-tier structure, including an added layer for general-purpose AI models, and its goals of building trust, harmonizing the internal market and protecting fundamental rights. He details the burden this creates: an 458-page text, high compliance costs, steep fines and unresolved practical questions such as fine-tuning, biometric categorization and AI literacy obligations. He closes with the Act's relief measures for smaller companies and ten concrete recommendations for organizations preparing for enforcement.https://www.youtube.com/embed/aiccyX_ezYs17402024-05-21T00:00:00+00:00yes https://riseof.ai/talks/the-european-data-strategy-damian-boeselager/https://i.ytimg.com/vi/tSAnvD_yOxk/hqdefault.jpgThe European Data Strategy – Damian Boeselager (Rise of AI Virtual Chat 2020)In this Rise of AI Virtual Chat from 2020, Fabian Westerheide interviews Damian Boeselager, Member of the European Parliament for Volt and member of the Greens/EFA group and the budget committee, about the European Union's data strategy and its relationship to AI regulation. Boeselager recounts co-founding the pan-European party Volt in 2017 in response to Brexit, Trump's election and rising nationalist parties, and explains why Volt joined the Greens group in the European Parliament to gain committee seats, including the budget committee. The two then discuss the EU's AI white paper, led by Commissioner Margrethe Vestager, and the separate data strategy pushed by Commissioner Thierry Breton, who argued the EU needs a data strategy because algorithms cannot be trained without data. Boeselager explains the EU's proposed risk-based framework for regulating AI by how much it infringes fundamental rights, the tension between European sovereignty (data security, control of critical infrastructure) and competitiveness (relying on more advanced US cloud providers), and how the EUR 750 billion Covid recovery fund could be spent on digital and green transformation with minimum spending thresholds Boeselager is pushing for.https://www.youtube.com/embed/tSAnvD_yOxk36602020-07-31T00:00:00+00:00yes https://riseof.ai/talks/the-european-entrepreneurial-way-adrian-locher/https://i.ytimg.com/vi/gwzLnv-8fvE/hqdefault.jpgThe European Entrepreneurial Way – Adrian Locher (Rise of AI Conference 2025)At Rise of AI 2025 in Berlin, Adrian Locher, Founder and General Partner of Merantix Capital, argues that early-stage AI investing succeeds through platform support rather than capital alone. He describes Merantix as a mix of venture studio and VC fund, backed by a EUR100 million fund, a roughly 1,500-person AI community on its Berlin campus, a 100-person consulting arm called Merantix Momentum, and the AI House event at the World Economic Forum in Davos. The firm invests in the application layer rather than infrastructure or tooling, and looks for products deeply embedded in client workflows, which Locher sees as more defensible than thin wrappers around existing AI models. He shares learnings from ten years of investing, including how Merantix uses its trust with European corporates to get early-stage startups signed as design partners before a product even exists, and describes five recurring founder personas in its portfolio. He closes by urging Europe to act and accept failure rather than keep discussing plans.https://www.youtube.com/embed/gwzLnv-8fvE19202025-05-21T00:00:00+00:00yes https://riseof.ai/talks/the-first-ai-product-for-railway-infrastructure-vlad-lata/https://i.ytimg.com/vi/Jn40TZ-0Hzo/hqdefault.jpgThe First AI Product for Railway Infrastructure – Vlad Lata (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Vlad Lata, Vice Chairman at KONUX, describes how his company built a predictive-maintenance product for railway switches. KONUX, then over 50 employees and having raised more than 50 million dollars, operates in Germany, Sweden and France and is expanding into Japan, China and the US. Lata frames the problem: in Germany alone 12 million passengers travel daily, one in five experiences a delay of more than six minutes, and half of passengers are dissatisfied, while maintenance rules date from the 1960s and 1970s and no longer match today's doubled train and cargo loads. He argues that building an AI product for such an industry requires three things together: domain expertise, IoT sensing, and AI, since existing railway systems were built for process control, not data analysis. KONUX attaches acceleration sensors to railway switches, converts the signal into vertical displacement to assess ballast condition, and applies predictive algorithms, following what Lata calls a strategic data acquisition cycle in which the product's immediate value to users drives more data and further product improvement.https://www.youtube.com/embed/Jn40TZ-0Hzo15002019-07-19T00:00:00+00:00yes https://riseof.ai/talks/the-future-of-ai-agents-pascale-fung/https://i.ytimg.com/vi/Um3b2D2WuqE/hqdefault.jpgThe Future of AI Agents – Pascale Fung (Rise of AI Conference 2025)At Rise of AI 2025 in Berlin, Pascale Fung, Director at Meta FAIR, argues that AI is entering a new era defined by autonomous, embodied agents rather than simple assistants. She traces Meta FAIR's history, from PyTorch and the first Llama model, developed in Paris, to the No Language Left Behind project covering more than 300 languages, and explains why FAIR insists on open-sourcing its models: only open science lets the community independently verify claims such as which model performs best. Fung calls 2025 the "year zero" of AI agents, distinguishing them from earlier assistants by their ability to carry out long, multi-step tasks autonomously. She then focuses on embodied agents, in wearable devices, avatars and robots, that must model both the physical world and a user's mental state, and warns that hallucination is far more dangerous once agents act physically rather than only answering text. FAIR is exploring JEPA-based world-modeling architectures to build agents that are objective-driven rather than merely trained to predict the next token. She closes with a video scenario of a future dinner party run with wearable and robotic assistance, illustrating how embodied agents could remove physical and mental chores from daily life.https://www.youtube.com/embed/Um3b2D2WuqE18602025-05-21T00:00:00+00:00yes https://riseof.ai/talks/the-future-of-vc-how-the-industry-gets-disrupted-christian-nagel/https://i.ytimg.com/vi/0NZuiMry3fo/hqdefault.jpgThe Future of VC: How the Industry Gets Disrupted – Christian Nagel (Rise of AI Summit 2020)At the Rise of AI Summit 2020, Dr. Christian Nagel, co-founder and managing partner of Earlybird Venture Capital, explains why he thinks the largely unchanged venture capital value chain, sourcing, screening, due diligence, closing and portfolio support, is about to be reshaped by AI. He traces the shift to an anecdote in which a US venture capital firm knew a promising Berlin entrepreneur that Earlybird had missed, prompting the firm to build its own tech-supported sourcing engine. That engine pulls from more than 100 sources, including GitHub, Product Hunt, public registries, social media, Crunchbase, PitchBook and CB Insights, to identify and enrich data on startups, and ranks those sources for reliability based on a study by the Technical University of Munich. The same study found the engine's picks matched the roughly 80 percent accuracy and recall of Earlybird's best human investors, though Nagel stresses the final investment decision still rests with people. He describes how auto-sourcing widened the firm's visible European deal flow and answers audience questions on gaming the algorithm, market sizing and current selection criteria.https://www.youtube.com/embed/0NZuiMry3fo16802020-11-30T00:00:00+00:00yes https://riseof.ai/talks/the-german-genius-invention-innovation-tina-kl-wer/https://i.ytimg.com/vi/0Dy7EsM64tY/hqdefault.jpgThe German Genius: Invention & Innovation – Tina Klüwer (Rise of AI Conference 2025)At Rise of AI 2025 in Berlin, Dr. Tina Klüwer, Director of AI Strategy at what she describes as Germany's federal ministry for research, technology and space (renamed from the education and research ministry the week before the talk), argues Germany suffers from a persistent gap between invention and innovation. She cites rankings placing Germany third worldwide in AI research publications, sixth in patents, ninth in AI startups and twelfth in enterprise AI adoption, calling this the German or European paradox: strong basic research, weaker commercialization. She describes a policy shift from funding research alone toward supporting businesses that adopt and build AI, including four regional AI service centers for SMEs and two EuroHPC AI factories built in Germany. She also previews a planned EU AI gigafactory initiative with up to five facilities across Europe, each with about 100,000 GPUs, for which Germany is seeking to be a host. A lively Q&A covers energy consumption, ministerial coordination, public trust and whether Germany is too late to the infrastructure race.https://www.youtube.com/embed/0Dy7EsM64tY18002025-05-21T00:00:00+00:00yes https://riseof.ai/talks/the-global-ai-landscape-hans-uszkoreit/https://i.ytimg.com/vi/Ba0XgeQz2oI/hqdefault.jpgThe Global AI Landscape – Hans Uszkoreit (Rise of AI Summit 2020)At the Rise of AI Summit 2020, Hans Uszkoreit, scientific director at DFKI in Berlin and founder and chief scientist of an AI company in Beijing, compares the AI strengths of the United States, China and Europe after nearly a year back in Europe following three years in China. Building on Kai-Fu Lee's comparison of the two AI giants, he argues Europe is not leading in AI for internet services, consumer electronics or finance, but holds strong chances in manufacturing, Industry 4.0 and enterprise AI, and in the next wave of AI that combines machine learning with explicit knowledge graphs. He describes the 'intelligent enterprise' as combining data, knowledge and business processes, while cautioning that AI cannot automate the most dynamic, high-level decisions. He argues Europe's persistent weakness is the last mile from basic research to scaled commercialization, and that German 'Angst' around data, illustrated by the country's Corona contact-tracing app, is holding AI adoption back. He proposes secured, trust-governed centralized data storage instead of current data protection norms, and closes discussing whether AI is dangerous and how enterprises can innovate despite AI's bias toward broad, data-rich topics.https://www.youtube.com/embed/Ba0XgeQz2oI19202020-11-20T00:00:00+00:00yes https://riseof.ai/talks/the-good-the-bad-and-the-ugly-daniel-jeffries/https://i.ytimg.com/vi/EMzEX8jrqJE/hqdefault.jpgThe Good, the Bad and the Ugly – Daniel Jeffries (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, science-fiction author and futurist Daniel Jeffries argues that despite loving the concept in his own fiction, he does not believe the technological singularity is near, because no one currently knows how to build artificial general intelligence or abstract reasoning. He traces AI's history as decades of failure and "winters," credits Geoffrey Hinton with keeping neural net research alive, and explains that people predict the future badly because they project a technology's current, flawed iteration forward instead of picturing a category maturing over time. He calls sentencing algorithms in US courts an example of the "ugly" side of AI, since black-box systems trained on biased historical data reproduce the same injustices against poor and disadvantaged people. He argues the more realistic future is not artificial general intelligence but narrow, "semi-alien" intelligence augmenting humans, illustrated by the MIT-covered "Rise of the Centaurs" chess result, and applies this to medical monitoring, smart homes and self-driving cars, cautioning that these benefits will roll out more slowly than people expect while automation, as in past eras, will create new jobs rather than eliminate work overall.https://www.youtube.com/embed/EMzEX8jrqJE15002018-06-10T00:00:00+00:00yes https://riseof.ai/talks/the-jedi-deepfake-grand-challenge-and-frontiers-in-ai-for-our-societie/https://i.ytimg.com/vi/JnIBwtNHkk4/hqdefault.jpgThe JEDI Deepfake Grand Challenge and Frontiers in AI for Our Societies – André Loesekrug-Pietri (Rise of AI Summit 2020)At the Rise of AI Summit 2020, Andre Loesekrug-Pietri, Executive Director of the Joint European Disruptive Initiative (JEDI), a body he describes as a European DARPA, argues that AI is both a threat to and a potential tool for democracy. Nine months earlier, around a hundred scientists, deep-tech founders and corporates, now several thousand across 29 countries, concluded that Europe cannot only play defense on technology and must invent breakthroughs, not just regulate. He argues AI-augmented decision-making, illustrated by aerospace predictive maintenance, could give democracies the long-term compass that authoritarian states already use, citing China's 2025 and 2049 plans against Europe's crisis-to-crisis management. He describes how fake news and platform-driven echo chambers undermine public debate, citing Cambridge Analytica and a claim that Donald Trump made 20,000 false statements in 1,300 days. He presents deepfakes, built on generative adversarial networks, as a frontier where detection is inherently hard, and announces JEDI's Deepfake Grand Challenge, targeting 99 percent detection faster than a video's own length. He also flags civilian surveillance uses of AI and proposes distributed face recognition and homomorphic encryption as privacy-preserving alternatives, arguing for transparency over bans.https://www.youtube.com/embed/JnIBwtNHkk419202020-11-20T00:00:00+00:00yes https://riseof.ai/talks/the-last-project-jonas-andrulis/https://i.ytimg.com/vi/Mw_EFcMmYvQ/hqdefault.jpgThe Last Project – Jonas Andrulis (Rise of AI Conference 2022)At Rise of AI 2022 in Berlin, Jonas Andrulis, a serial entrepreneur whose latest company is Aleph Alpha and a former AI R&D manager at Apple, asks what counts as work and how AI is already changing it. He argues humanity's work has shifted from basic survival tasks, now largely automated, into knowledge work, innovation and entertainment, and cites an Open Philanthropy report estimating transformative AI around 2030. He explains large language models as "world models" trained to predict how any piece of human-written text continues, then demonstrates Aleph Alpha's model answering factual questions, translating, and reading a company's quarterly report to answer a free cash flow question. He shows multimodal extensions built at Aleph Alpha's Heidelberg lab, which he says formed part of the basis for DeepMind's Flamingo, including image reasoning, retained world knowledge, and even a made-up word the model produces. He also demonstrates clear failure cases, including inconsistent and language-dependent answers and a wrongly generated image, and closes by predicting that intelligence, unlike cloud infrastructure, will consolidate into general layers owned by a few key players.https://www.youtube.com/embed/Mw_EFcMmYvQ16202022-06-13T00:00:00+00:00yes https://riseof.ai/talks/the-new-ai-florian-dohmann/https://i.ytimg.com/vi/4qUOzLkDmJM/hqdefault.jpgThe New AI – Florian Dohmann (Rise of AI Conference 2022)At Rise of AI 2022 in Berlin, Florian Dohmann, founder of the Berlin-based agency Birds on Mars, argues for perspectives on AI beyond automation and efficiency, aiming to make it social, creative and climate-friendly. He opens with an enterprise example, a project with Deutsche Bahn predicting parking availability near German train stations, to illustrate that most effort in applied machine learning goes into data preparation and governance rather than the model itself, while the most user-facing part delivers the most value. He then describes several long-running side projects: the 'Artificial Muse,' a five-year collaboration with painter Roman Lipsky in which an AI trained on his digitized paintings generates new visual inspiration; a project bringing AI-based creative tools to people with mental and physical disabilities; an album with the band Mouse on Mars built on a technique he calls 'vector hacking' to semantically manipulate a voice-synthesis model; and Q Trees, a Berlin project using satellite, sensor and public data to predict which city trees most urgently need water as the climate warms.https://www.youtube.com/embed/4qUOzLkDmJM14402022-06-13T00:00:00+00:00yes https://riseof.ai/talks/the-new-german-ai-wave-startup-signals-and-founder-trends-hauke-hansen/https://i.ytimg.com/vi/LJ-AOLD0bzU/hqdefault.jpgThe New German AI Wave: Startup Signals and Founder Trends – Hauke Hansen (Rise of AI Conference 2026)At Rise of AI 2026 in Berlin, Dr. Hauke Hansen, founding partner of AI Fund, argues that German and European AI is not weak but misunderstood, speaking from the perspective of an AI venture investor. He opens with an economic diagnosis: Germany's GDP has grown only 1.8 times over 30 years, far behind the US, while private investment has fallen and public spending has kept rising, opening a 25 percent gap. He links today's growth almost entirely to AI, which has gone from 18 percent to over 60 percent of global VC spending in five years, and frames it as the fifth industrial revolution, following energy, electricity, compute and data, likely to unfold in around 17 years rather than the roughly 100 years earlier revolutions took. He describes an autonomous AI future built on the agentic economy, physical AI, AI memory, and vertical AI specialists, then argues AI will reshape rather than eliminate work, hitting midskill roles hardest. He closes with data on what makes European AI unicorns succeed and a call to also bring Germany's midsize companies into the wave.https://www.youtube.com/embed/LJ-AOLD0bzU19202026-07-15T00:00:00+00:00yes https://riseof.ai/talks/the-next-decade-of-ai-fabian-westerheide/https://i.ytimg.com/vi/9PEcnyhjBlo/hqdefault.jpgThe Next Decade of AI – Fabian Westerheide (Rise of AI Summit 2020)At the Rise of AI Summit 2020, held online with more than 1,500 registered viewers, Fabian Westerheide, CEO of Rise of AI and of Asgard Capital, reviews the last decade of AI and previews the next. He traces his own path from discovering Ray Kurzweil's ideas in 2014, founding Asgard Capital as an early AI-dedicated venture fund, and hosting small gatherings in a Berlin hacker space, through 2016, when AlphaGo's win over Lee Sedol made AI mainstream and pushed China to prioritize it, to 2017-2019, when AI became big business, then political as governments published national AI strategies. He argues that in 2020 AI is less about vision and more about execution, with growing ecosystems but a shortage of talent, and that the internet is fragmenting into distinct American, Chinese and European blocks with different data rules. Looking ahead, he expects AI regulation, explainability requirements and debates over taxing AI-generated value, alongside tension between digitalization and sustainability and a widening conflict over privacy versus safety. He closes by arguing that AI's purpose should be to help people live longer and happier, and answers audience questions on European competitiveness and superintelligence risk.https://www.youtube.com/embed/9PEcnyhjBlo18002020-11-20T00:00:00+00:00yes https://riseof.ai/talks/the-post-corona-world-daniel-jeffries/https://i.ytimg.com/vi/XdTMzpLZLFw/hqdefault.jpgThe Post Corona World – Daniel Jeffries (Rise of AI Virtual Chat 2020)At a Rise of AI Virtual Chat recorded live on 22 May 2020, host Fabian Westerheide talks with science-fiction author and technologist Daniel Jeffries about life after the first wave of COVID-19. Jeffries argues the pandemic is not past its peak and predicts further supply-chain disruptions, business closures and mass unemployment, especially in countries without strong health infrastructure. He describes a results-only work environment as the ideal setup for knowledge workers, criticizes commuting and most in-person business conferences as low-value, and says virtual events have cut production costs dramatically. He warns that crisis-driven surveillance and contact-tracing technology, once introduced, tends to persist through open-ended "sunset provisions," citing the USA PATRIOT Act as precedent, and criticizes governments and health authorities for downplaying the effectiveness of masks. On the upside, he expects accelerated open science, faster drug and antibody development, and overdue digitalization of bureaucracy. Asked whether decentralized AI could prevent misuse, he answers no, because algorithms simply encode the biases of the people who build them, regardless of how centralized the system is. The conversation closes with a question on the tyranny of the commons applied to mask-wearing.https://www.youtube.com/embed/XdTMzpLZLFw37802020-06-16T00:00:00+00:00yes https://riseof.ai/talks/the-scaling-laws-of-ai-why-neural-networks-continue-to-grow-adam-grzyw/https://i.ytimg.com/vi/NiRAIiR-xYE/hqdefault.jpgThe Scaling Laws of AI: Why Neural Networks Continue to Grow – Adam Grzywaczewski (Rise of AI Summit 2020)At the Rise of AI Summit 2020, Adam Grzywaczewski, senior deep learning data scientist at NVIDIA, discusses the scaling laws that govern how increasing model and dataset size reliably improves model performance. According to the talk description, the session opens with a deep dive into this relationship between scale and performance, then covers the practical challenges of working with large models, including the costs associated with assembling and using large datasets. The talk concludes by connecting these scaling approaches to some of the biggest breakthroughs achieved in natural language processing and computer vision. The automatic transcript for this recording failed and is not usable, so this page is built only from the talk's title, chapter structure and YouTube description rather than the spoken content itself; no direct claims, numbers or examples from the talk can be reproduced here beyond what the description states.https://www.youtube.com/embed/NiRAIiR-xYE15602020-11-30T00:00:00+00:00yes https://riseof.ai/talks/the-social-and-economic-impact-of-artificial-intelligence-ehssan-daria/https://i.ytimg.com/vi/VF_Snoi8nOg/hqdefault.jpgThe Social and Economic Impact of Artificial Intelligence – Ehssan Dariani (Rise of AI Conference 2016)At Rise of AI 2016 in Berlin, Ehssan Dariani, an economist and entrepreneur who founded the largest social network in German-speaking Europe before Facebook, argues that discussions of artificial intelligence and the singularity ignore social and political consequences. He says the world today is the best it has ever been, citing rising life expectancy and sharply lower war deaths since 1945, and argues terrorism carries little real risk but a large psychological effect, which a more statistically literate public would resist better. He predicts the Middle East and Africa will become more like Western Europe within two to three decades, pointing to secularization in Iran as an early sign. On the singularity itself, he compares skepticism about machines surpassing human intelligence to asking how apes created humans, framing it as an evolutionary process rather than a deliberate one. On jobs, he predicts most people will eventually live like today's wealthy who do not need to work, but warns that network effects are concentrating wealth and power in a small number of technology companies, and that groups such as displaced taxi drivers need an unconditional basic income funded by heavily taxing large tech corporations. He also argues for legalizing drugs.https://www.youtube.com/embed/VF_Snoi8nOg7202016-02-29T00:00:00+00:00yes https://riseof.ai/talks/the-state-of-ai-in-2019-fabian-westerheide/https://i.ytimg.com/vi/D67fUnekpIg/hqdefault.jpgThe State of AI in 2019 – Fabian Westerheide (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, founder Fabian Westerheide opens the conference with an overview of the state of AI. He recalls that the event started five years earlier as a small meetup called The Singularity Is Near in a Berlin hackerspace and has grown to about 800 attendees. Drawing on an AI Index study he worked on with Stanford University, he ranks the United States first globally, citing its research universities and large tech companies, and China second, noting a focused national strategy, abundant data and roughly 130 billion US dollars invested in AI. He argues Europe lags behind, lacking a coherent political agenda, large digital companies, enough startups and capital, despite strong research institutions such as DFKI and Max Planck. He describes AI becoming political, citing France's national strategy and a less concrete German one, and becoming big business, with the conference's own exhibition space growing. He argues most companies are not ready for AI because they have not digitized their data, and that deep learning, while not over, has stopped surprising researchers. He closes with open questions on ethics, bias and AGI, and announces the next conference date.https://www.youtube.com/embed/D67fUnekpIg12002019-07-01T00:00:00+00:00yes https://riseof.ai/talks/the-strategic-importance-of-ai-ethics-sarah-j-becker/https://i.ytimg.com/vi/R_UDtSJNGW4/hqdefault.jpgThe Strategic Importance of AI Ethics – Sarah J. Becker (Rise of AI Conference 2024)At Rise of AI 2024 in Berlin, Dr. Sarah J. Becker, Partner at Deloitte, argues that AI ethics is a strategic enabler rather than a compliance afterthought. Opening with a personal story about a panic attack on a flight, she describes how people accept transformative technologies without questioning them until something forces reflection, and how new technologies tend to produce polarized reactions, either overestimating their potential or fearing humans will be overrun. She presents survey data showing that 79% of decision-makers already using generative AI report ethical concerns, yet only one in five companies has an ethical framework in place. Drawing on a study of AI ethics guidelines, she shows transparency as the most cited value worldwide, with explainability more prominent in Europe and fairness more prominent in East Asia. She warns that many organizations are currently swinging from early AI experimentation toward heavy control through compliance, legal and security functions, which raises the barrier to innovation. Her closing message is that ethics cannot be delegated and needs real resources, not just guideline documents.https://www.youtube.com/embed/R_UDtSJNGW412002024-05-21T00:00:00+00:00yes https://riseof.ai/talks/the-third-wave-of-ai-kristian-kersting/https://i.ytimg.com/vi/LlrHY02AA-o/hqdefault.jpgThe Third Wave of AI – Kristian Kersting (Rise of AI Virtual Chat 2020)In this Rise of AI Virtual Chat from August 2020, host Fabian Westerheide talks with Kristian Kersting, professor for AI and machine learning at TU Darmstadt, about what Kersting calls the "third wave" of AI: combining reasoning, learning and acting through hybrid, knowledge-driven systems. Kersting explains GPT-3's excitement as the first sign of a system handling many tasks it was not explicitly trained for, describes deep learning as "differentiable programming," and argues the field needs a dedicated high-level programming language in which learning algorithms are first-class citizens, so domain experts like biologists do not need to specify network architectures themselves. He describes his own research combining probabilistic programming, statistical relational learning and deep networks, and his work leading the planned Hessian cross-university AI institute, which he calls in the talk the “Tensor Institute” (following, he explains, a naming progression from a “Parameter Institute” to the Vector Institute), bringing together universities across the state. On ethics, he argues bias findings in AI models mirror human bias rather than being an AI-specific problem, and rejects blaming AI for autonomous weapons rather than the humans and game theory behind weapons development. He is skeptical of the term AGI and says true intelligence means being a robust general problem solver, not an optimal one.https://www.youtube.com/embed/LlrHY02AA-o36002020-08-20T00:00:00+00:00yes https://riseof.ai/talks/the-true-revolution-lies-ahead-of-us-ramin-assadollahi/https://i.ytimg.com/vi/ugzN7W7q2Gk/hqdefault.jpgThe True Revolution Lies Ahead of Us – Ramin Assadollahi (Rise of AI Conference 2025)At Rise of AI 2025 in Berlin, Ramin Assadollahi, founder and CEO of ExB Group, argues that AI is about to transform longevity and preventive medicine. He frames the goal as reaching a personal 'longevity escape velocity', where each medical advance extends lifespan long enough to reach the next one, referencing Aubrey de Grey's idea that the first 1,000-year-old may be only ten years younger than the first 150-year-old. He organizes longevity research into four systems: genes, the microbiome, the central nervous system and the immune system, which he calls a post-processor for the other three. He explains that conventional drug development costs up to 2.5 billion dollars and 10-15 years per drug, with under 11% of candidates reaching phase one trials, and proposes that AI-driven digital twins and in-silico simulation, an approach he compares to 'vibe coding', could make drug development interactive and personalized. He surveys wearables such as implantable EEGs, glucose-and-hydration sensors and sweat monitors as new sources of fast personal data, and closes by calling for a meta-framework linking simulations across biological levels and for changed legislation and data access to support personalized medicine.https://www.youtube.com/embed/ugzN7W7q2Gk20402025-05-21T00:00:00+00:00yes https://riseof.ai/talks/think-big-start-small-grow-fast-ronny-fehling/https://i.ytimg.com/vi/z04Swy3vebw/hqdefault.jpgThink Big, Start Small, Grow Fast – Ronny Fehling (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, Ronny Fehling, Head of AI at BCG GAMMA, argues that companies unlock AI's business value by thinking big about the opportunity while starting with one to three concrete lighthouse projects. Drawing on client work rather than research, he contrasts rule-based expert systems with machine learning systems that derive rules from past outcomes, and stresses that most enterprise data is unstructured and still untapped. He walks through two real cases: a manufacturing client where natural language processing matched new quality issues against past written notes, and a general ledger project where clustering and NLP mapped hundreds of thousands of multi-language invoices to cost categories. Both cases reveal a common lesson: getting AI to produce actionable recommendations is only part of the challenge, since humans interacting with the system can introduce their own biases into it. Fehling closes by urging European companies to rethink entire value chains under AI rather than only automate existing processes, arguing Europe's manufacturing base combined with its data gives it a real advantage if used well.https://www.youtube.com/embed/z04Swy3vebw13202018-06-08T00:00:00+00:00yes https://riseof.ai/talks/towards-a-general-theory-of-intelligence-peter-morgan/https://i.ytimg.com/vi/qZf4f8nHKKU/hqdefault.jpgTowards a General Theory of Intelligence – Peter Morgan (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Peter Morgan, CEO of Deep Learning Partnership, argues that deep learning cannot lead to artificial general intelligence and proposes a physics-based alternative. He defines intelligence as an agent's adaptation to its environment and argues there are many distinct types of intelligence — physical, spatial, musical, linguistic, social, emotional — not just the logical-mathematical kind that deep learning approximates. He traces how biology builds intelligence hierarchically, from chemical-gradient navigation in bacteria without neurons, through the roughly 130-neuron nervous system of C. elegans and the million-neuron bumblebee, up to the human brain's roughly 100 billion neurons organized into repeating cortical columns. Comparing digital hardware such as Google's TPU and the Summit supercomputer to neuromorphic systems like SpiNNaker and BrainScaleS, he argues that brain-like hardware that combines memory and processing is a necessary step toward AGI, since digitally simulating the brain is far less efficient than biology itself. He proposes grounding a general theory of intelligence in physics, specifically the principle of least action, and highlights active inference, tied to Karl Friston's free energy principle, as the theoretical approach he finds most promising among several decades-old research programs.https://www.youtube.com/embed/qZf4f8nHKKU21002019-07-17T00:00:00+00:00yes https://riseof.ai/talks/towards-superintelligence-paths-pitfalls-and-europe-s-choice-hans-uszk/https://i.ytimg.com/vi/Fyhjgb4re0o/hqdefault.jpgTowards Superintelligence: Paths, Pitfalls and Europe’s Choice – Hans Uszkoreit (Rise of AI Conference 2026)At Rise of AI 2026 in Berlin, Prof. Dr. Hans Uszkoreit of DFKI revisits a talk he gave at an early, then little-known edition of Rise of AI nine years earlier, titled 'Superintelligence: Will machines be smarter than us?', and argues that the field has changed completely since then, from narrow, knowledge-engineered AI to large language models trained on text, a shift triggered by the transformer paper published a month after his original talk. He argues today's LLMs have super-knowledge and super-eloquence far beyond any human, but lack autonomy, memory and continual learning, comparing them to a narcoleptic Alzheimer's patient. Using the Cattell-Horn-Carroll model of fluid and crystallized intelligence, he argues that current benchmarks measuring how close GPT-4 and GPT-5 are to human intelligence are flawed because they only test tasks humans can already do. He surveys new memory-architecture research at Google, Stanford, Nvidia and by Sepp Hochreiter as the likely path to closing the remaining gap, calls the resulting systems very dangerous, dismisses claims that LLMs use excessive energy or water as illusions, and argues Europe can still catch up in frontier AI with one to three well-funded, well-staffed labs, but is currently talking rather than acting.https://www.youtube.com/embed/Fyhjgb4re0o18002026-07-15T00:00:00+00:00yes https://riseof.ai/talks/trends-in-ai-as-told-by-the-2024-ai-index-report-nestor-maslej/https://i.ytimg.com/vi/6KE0nCFPQKc/hqdefault.jpgTrends in AI as Told by the 2024 AI Index Report – Nestor Maslej, Thomas Neubert (Rise of AI Conference 2024)At Rise of AI 2024 in Berlin, Nestor Maslej, Research Manager and AI Index Editor-in-Chief at Stanford's Institute for Human-Centered AI, joins Thomas Neubert, founder of the Transatlantic AI eXchange, in a fireside chat that condenses findings from the 2024 AI Index Report. Maslej walks through headline trends: AI systems now exceed human performance on many benchmark tests, training costs for frontier models have risen sharply (GPT-4 an estimated 80 million dollars, Gemini 191 million dollars), and only a handful of companies can afford to build such systems. He argues Europe is not out of the running on large language models even without matching the biggest training budgets, since there is value in making models more efficient. He cites evidence that AI tools speed up work by 26 to 73 percent across studies, that a McKinsey survey found 42 percent of managers report cost decreases and 59 percent report revenue increases from AI, and that Google's AlphaMissense model raised annotation coverage of human protein mutations from 0.1 percent to 89 percent. He closes on survey data showing rising public nervousness about AI in every country sampled, most pronounced in Germany, the US and other Western nations.https://www.youtube.com/embed/6KE0nCFPQKc16202024-05-21T00:00:00+00:00yes https://riseof.ai/talks/trust-in-ai-is-your-ai-compliant-and-explainable-florens-gressner/https://i.ytimg.com/vi/_q3xXfqYyOA/hqdefault.jpgTrust in AI: Is Your AI Compliant and Explainable? – Florens Gressner (Rise of AI Conference 2022)At Rise of AI 2022 in Berlin, Florens Gressner, co-founder and CEO of neurocat, argues that trust in AI has to be built through systematic risk testing, not assumed. Speaking on the Applied AI Stage, he explains that neurocat has spent nearly five years evaluating and mitigating risk for safety- and security-critical AI systems, running more than 25 customer projects including autonomous driving use cases. He walks through the European Union's then-pending AI Act, which classifies AI applications by risk and imposes testing, risk-mitigation and transparency requirements on high-risk categories such as critical infrastructure, credit and job scoring, law enforcement and biometrics. His central technical argument is that ordinary performance metrics fail high-risk AI systems because they average over all data and dilute rare but severe edge cases; he defines risk instead as severity times exposure and argues each relevant scenario, including corrupted or adversarially manipulated data, must be tested separately. He describes neurocat's automated testing platform, built to integrate into machine-learning pipelines, and closes by predicting the AI Act will become mandatory within about two years and answering audience questions on strong AI, public trust, certification and healthcare.https://www.youtube.com/embed/_q3xXfqYyOA18002022-06-13T00:00:00+00:00yes https://riseof.ai/talks/trustworthy-ai-for-the-physical-world-ulli-waltinger/https://i.ytimg.com/vi/0hkN8PSTomk/hqdefault.jpgTrustworthy AI for the Physical World – Ulli Waltinger (Rise of AI Summit 2020)At Rise of AI Summit 2020 in Berlin, Ulli Waltinger, Technology Head of the Siemens AI Lab, argues that industrial AI has moved past the question of whether machine learning adds value and must now be put into pervasive operation across energy management, mobility, additive manufacturing and shop-floor systems. He distinguishes two application classes: 'selfish systems' that increase machine autonomy, and 'digital companions' that support human decision-making. Because labeling all industrial data is infeasible, Waltinger says the field is shifting from purely supervised learning toward self-supervision combined with domain expertise. He stresses starting from the deployed business problem and the 'minimal justifiable improvement' rather than chasing proof-of-concept accuracy, and names data readiness, active learning, explainability, federated learning and robustness against domain shift as the core applied-research questions his lab works on with partners. He closes with three takeaways: aim for production, not prototypes; define the minimal justifiable improvement and what not to do; and treat trustworthiness, explainability, robustness and security as imperative for industrial AI.https://www.youtube.com/embed/0hkN8PSTomk17402020-11-30T00:00:00+00:00yes https://riseof.ai/talks/trustworthy-ai-opening-the-black-box-beril-sirmacek/https://i.ytimg.com/vi/80m92MhQsxw/hqdefault.jpgTrustworthy AI: Opening the Black Box – Beril Sirmacek (Rise of AI Virtual Chat 2020)In this Rise of AI Virtual Chat from May 2020, host Fabian Westerheide talks with Dr. Beril Sirmacek, assistant professor at Jönköping University, about what trustworthy AI means and how explainability fits into it. Sirmacek illustrates trust using an analogy of an alien being told an animal is a cat: trust can come either from a system's track record of good results or from an explanation of the reasoning behind a decision. She structures trustworthiness and ethics into three subtopics: GDPR and data privacy, data security, and responsible use, and describes explainability as one mathematical tool within that larger field, not the whole answer. Using examples including elderly-care robots, cancer-stage classification and credit scoring, she discusses named tools such as LIME and SHAP, the trade-off between model complexity and explainability, and the case for hybrid systems combining feature engineering with smaller neural networks. She also addresses AGI, EU AI regulation discussed in the European Commission's recent white paper, and audience poll results on who should be responsible for AI's impact and who should define the values it acts on.https://www.youtube.com/embed/80m92MhQsxw36602020-05-04T00:00:00+00:00yes https://riseof.ai/talks/trustworthy-ai-opening-up-the-black-box-beril-sirmacek/https://i.ytimg.com/vi/f9uxdlJ5W3s/hqdefault.jpgTrustworthy AI: Opening Up the Black Box – Beril Sirmacek (Rise of AI Summit 2020)At the Rise of AI Summit 2020, Beril Sirmacek, assistant professor in computer science and informatics at Jönköping University, argues that trustworthy AI means opening up the black box of machine learning models rather than trusting them on performance numbers alone. She frames trust as a basic human need alongside food and safety, citing Abraham Maslow's 1943 theory of human motivation, and argues that businesses deploying AI face the same requirement: users will only pay for a model's decisions if they can trust them. She illustrates the problem with concrete cases: search engines linking the name Latanya Sweeney to arrest-related ads because of racial bias, a recidivism-risk model that misjudged two defendants named Bernard and Dylan, adversarial noise that turns a panda into a misclassified animal, and a wolf-versus-husky classifier that reached 99.9 percent accuracy by detecting snow in the background instead of the animal. She presents explainable AI (XAI) methods such as SHAP feature importance as tools for inspecting training data, models and inputs, stressing that the right explanation depends on who is asking and that trust itself has no quantitative measure. She closes by imagining real-time XAI feedback loops between AI systems and their users.https://www.youtube.com/embed/f9uxdlJ5W3s18002020-11-30T00:00:00+00:00yes https://riseof.ai/talks/ultimate-ai-augment-do-not-replace-reetu-kainulainen/https://i.ytimg.com/vi/eRVglElGWk0/hqdefault.jpgUltimate AI: Augment, Do Not Replace – Reetu Kainulainen (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Reetu Kainulainen, CEO and co-founder of ultimate.ai, argues that AI should augment human customer service agents rather than replace them with chatbots. She traces customer service from 1960s call routing through the dot-com era, cloud-based contact centers and, later, instant-messaging channels, noting that 4 percent of OECD employees, an estimated 7 million people in Europe, now work in contact centers, at an average enterprise cost of over 50 million dollars a year with up to 300 percent annual staff turnover. She says many companies tried pure chatbot automation but found the technology too shallow to replace human conversation. Instead, ultimate.ai builds an AI backbone integrated with tools such as Salesforce, Zendesk and Genesys, using deep neural networks trained on historical chat and email data to give agents real-time recommended answers, with a feedback loop that improves accuracy as agents accept or modify suggestions. She describes handling complex languages like Finnish, using clustering to structure unlabeled conversation data, and reports customer results including one user whose agents now take 96 percent of answers from recommendations, and response times cut roughly in half.https://www.youtube.com/embed/eRVglElGWk012002019-07-20T00:00:00+00:00yes https://riseof.ai/talks/unblocking-bureaucracy-georg-schlenkhoff/https://i.ytimg.com/vi/KmRw4rdRfUo/hqdefault.jpgUnblocking Bureaucracy – Georg Schlenkhoff, Oliver Stuke (Rise of AI Conference 2025)At Rise of AI 2025 in Berlin, Georg Schlenkhoff (Mistral AI) and Oliver Stuke (Capgemini Invent) argue that Europe, despite a widespread narrative of having fallen behind in AI, is building real momentum toward sovereign generative AI, and show how that stack can be applied to unblock public-sector bureaucracy. Schlenkhoff frames sovereignty as owning infrastructure, technology and data, citing figures that only 3 percent of European R&D spending goes to technology and software and that Europe consumes 20 percent of global chips while producing only 9 percent. Stuke points to recent political momentum, including a German conference of minister presidents' sovereignty declaration, a Dutch parliamentary declaration and the EU's 200-billion-euro continent AI action plan, and presents a layered sovereign stack built with partners including StackIT, Aleph Alpha, Mistral, Fraunhofer, Demos and Atlas Systems. They walk through a concrete application in Germany's Ministry of Interior, where an AI system checks planning applications for wind turbines against legal requirements and drafts notices to applicants, while stressing that German administrative law bars fully autonomous decisions and requires a human in the loop. Audience questions cover adversarial attacks, change management and ethical data handling.https://www.youtube.com/embed/KmRw4rdRfUo19802025-05-21T00:00:00+00:00yes https://riseof.ai/talks/unleashing-genai-for-industries-feiyu-xu/https://i.ytimg.com/vi/Uy2sPRUS9Hc/hqdefault.jpgUnleashing GenAI for Industries – Feiyu Xu (Rise of AI Conference 2024)At Rise of AI 2024 in Berlin, Feiyu Xu, Non-Executive Director of Airbus Group and board member at ZF, argues that generative AI marks a shift from AI that classifies and recognizes to AI that creates content, which she says brings it structurally closer to human intelligence and makes adoption easier because companies no longer need large teams of data engineers to label data. She notes that at least seven of the world's ten largest public companies by market cap are AI-first, and situates the moment against the 2023 OpenAI leadership crisis, the Hollywood writers' protests against AI, and the EU AI Act. She lays out a framework for positioning a company in the generative AI ecosystem across infrastructure, models and applications, data ownership and access, and industry vertical, and recommends companies start with business-process automation before moving to more intelligent products. She then details persistent gaps: large language models lack deep engineering, chemical and geometric domain knowledge, struggle with real-time short-term forecasting, and cannot reliably handle escalated customer complaints or troubleshooting, so she recommends a holistic data governance strategy and treating GenAI as one part of a larger system rather than a complete solution.https://www.youtube.com/embed/Uy2sPRUS9Hc16202024-05-21T00:00:00+00:00yes https://riseof.ai/talks/update-on-germany-s-ai-strategy-sabine-d-ring/https://i.ytimg.com/vi/8C1Adxi0NwQ/hqdefault.jpgUpdate on Germany’s AI Strategy – Sabine Döring (Rise of AI Conference 2024)At Rise of AI 2024 in Berlin, Sabine Döring, State Secretary at Germany's Federal Ministry of Education and Research, presents an update on the country's AI strategy. She argues AI is a once-in-a-century opportunity that Germany must help shape, not just use, so that it is not left behind by the US and China. She outlines a cultural shift starting in schools through the BMBF's Startchancen program and a renegotiated Digitalpakt 2.0, and cites that 34% of 14 to 20 year olds already use AI, mostly not to cheat. On research, she points to six AI centers of competence, 150 AI professorships and roughly 500 million euros invested in 2024, nearly double the previous legislative term, funding better AI methods, early-career and women researchers, and medical applications. She reports 40% more German AI patent applications since 2019 and 341 AI startups founded in 2023. She stresses European cooperation, highlighting the Jupiter exascale supercomputer, and defends the AI Act's research exemption, closing by citing a semiconductor-company CEO's comparison of AI to electricity, a foundational technology rather than an optional appliance.https://www.youtube.com/embed/8C1Adxi0NwQ7202024-05-20T00:00:00+00:00yes https://riseof.ai/talks/using-sound-and-ai-for-low-cost-3d-environment-perception-tobias-bahne/https://i.ytimg.com/vi/uEg2azch3tg/hqdefault.jpgUsing Sound and AI for Low-Cost 3D Environment Perception – Tobias Bahnemann (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Tobias Bahnemann, co-founder and managing director of Toposens, presents a 3D ultrasound sensor that uses sound and AI to give robots and vehicles low-cost close-range environment perception. Comparing the idea to Batman's citywide sonar in The Dark Knight, he explains that Toposens sends out high-frequency sound, captures reflections with three microphones, and processes them on a small chip, the SoundVision 1, into a 3D point cloud, without needing light and while generating only 3 to 5 megabytes of data per hour, small enough for on-device AI processing. He argues the technology fills a gap left by camera and lidar systems, which struggle at close range, in poor lighting, with glass, or at prices that keep them out of many products, citing failures such as unreliable autonomous parking and undetected curbs. He describes four prerequisites for training reliable neural nets on this data (reliable, precise, dense and large datasets) and Toposens' staged roadmap from detecting static objects to dynamic ones and eventually predictive understanding, alongside partnerships with Nvidia and Infineon, named customers, and an ongoing funding round.https://www.youtube.com/embed/uEg2azch3tg13202019-07-19T00:00:00+00:00yes https://riseof.ai/talks/virtual-human-agent-for-smart-city-atsushi-ishii/https://i.ytimg.com/vi/KSqkHW3QOfU/hqdefault.jpgVirtual Human Agent for Smart City – Atsushi Ishii (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Atsushi Ishii, CEO of the Tokyo-based startup Couger, presents Connectome, the technology behind Couger's Virtual Human Agent, a character with simulated senses, emotion and intelligence meant to become a new, more natural interface than keyboards, touchscreens or voice assistants. He grounds the pitch in four areas of prior work: character AI for games, a learning simulator that Honda uses for autonomous cars and robots, cloud robotics developed with a team from the Amazon Robotics Challenge, and enterprise blockchain for secure data sharing. He plays demo videos of the Virtual Human Agent, named Rachel, operating in augmented reality on a tablet and answering questions live in a German television interview, and explains how it detects and mirrors human facial expressions. Ishii describes an architecture that combines machine learning, which predicts a single best answer from data, with gaming AI, which builds a believable world, plus components for personality, semantic and episodic memory, and emotion. He closes by outlining planned use cases, including gaming, interactive digital signage and in-car assistants, and an upcoming SDK and marketplace for outside developers to build their own virtual human agents.https://www.youtube.com/embed/KSqkHW3QOfU13802019-07-17T00:00:00+00:00yes https://riseof.ai/talks/we-may-head-to-an-ai-winter-danko-nikolic/https://i.ytimg.com/vi/sgbd6eAj-OE/hqdefault.jpgWe May Head to an AI Winter – Danko Nikolic (Rise of AI Conference 2017)At Rise of AI 2017 in Berlin, Danko Nikolic argues that the AI field risks repeating past AI winters because it has forgotten the original meaning of "strong AI." He explains that the term, coined by a philosopher in the 1960s or 70s, originally described biological intelligence, such as a dog's, as strongly intelligent because it learns from very few examples with limited resources, in contrast to today's usage of strong AI as synonymous with human-level AGI. Estimating that humans can distinguish between 10 to the power of 20 and 10 to the power of 48 things without new learning, against roughly 100,000 for contemporary AI systems, he argues that scaling AI to human-level intelligence requires resources growing far faster than linearly, making it effectively unaffordable with today's approach. He warns that over-promising based on small-scale demos, as happened with a major Japanese government AI project, is what historically triggers AI winters and could again trigger an economic crisis. He closes by describing his own startup's experiment, in which an evolved agent learned to recognize handwritten digits from only three training examples per character.https://www.youtube.com/embed/sgbd6eAj-OE16202017-05-25T00:00:00+00:00yes https://riseof.ai/talks/welcome-state-of-ai-2024-fabian-westerheide/https://i.ytimg.com/vi/LeuM9NLcFN0/hqdefault.jpgWelcome & State of AI 2024 – Fabian Westerheide (Rise of AI Conference 2024)At Rise of AI 2024, Fabian Westerheide, CEO and Partner at Rise of AI and AI.Fund, opens the eighth edition of the conference with a review of the AI market and a call to action for German and European policy. He reports a hard cap of 300 onsite attendees with an overbooked waiting list and 1,600 livestream viewers from over 50 nations. He describes 2024 as the year of generative AI, with billions in new funding flowing mostly into foundation models even as the broader VC market declined, and names Nvidia and Microsoft as the year's biggest winners. He argues the US-Europe gap is widening and that 95 percent of global users rely on OpenAI, while China quietly built over 100 foundation models in six months. He uses the talk to launch his book on the state of AI, written partly with AI assistance, and lays out policy demands: a digital government, tax reform that favors labor less than investment, incentives for AI adoption, sovereign European foundation models, reinvestment by the super-rich, and AI and coding education starting in kindergarten.https://www.youtube.com/embed/LeuM9NLcFN013802024-05-20T00:00:00+00:00yes https://riseof.ai/talks/welcome-state-of-ai-2026-fabian-westerheide/https://i.ytimg.com/vi/LT6vXXS8ihw/hqdefault.jpgWelcome & State of AI 2026 – Fabian Westerheide (Rise of AI Conference 2026)At Rise of AI 2026 in Berlin, Fabian Westerheide, co-founder of Rise of AI and founding partner at AI.Fund, opens the conference's 10th anniversary edition with a retrospective on a decade of AI. He argues 2016 was the industry's real turning point, when deep learning research (DeepMind, reemerging neural networks running on Nvidia chips) took AI from a niche topic to a political one, with China's rise and OpenAI's founding both dating from that period. He traces a shift in the conference's own recurring themes from discussing AI's potential to discussing implementation, scaling and, increasingly, technological sovereignty. Westerheide names lessons learned over ten years: transformation inside companies and governments moves slower than expected, regulation keeps expanding, and capital availability, more than talent or ecosystems, decides which regions' AI companies scale, with Europe lagging the US and China. He says jobs are shifting rather than disappearing and that AI agents are becoming core infrastructure. He closes with a call to start from concrete problems rather than technology, and not worry about being first. A short on-stage interview follows about the event's history and its founders.https://www.youtube.com/embed/LT6vXXS8ihw15002026-07-15T00:00:00+00:00yes https://riseof.ai/talks/what-if-future-optimism-with-mario-brandenburg-mario-brandenburg/https://i.ytimg.com/vi/Ew4MDjRsFKc/hqdefault.jpgWhat If…? Future Optimism with Mario Brandenburg – Mario Brandenburg (Rise of AI Virtual Chat 2020)In this Rise of AI Virtual Chat from July 2020, host Fabian Westerheide talks with Mario Brandenburg, a member of the German Bundestag for the FDP who sits on the Digital Agenda Committee and works on AI, genetic engineering, blockchain and drug policy, about a series of speculative what-if questions. Brandenburg argues that if machines eventually did all jobs, people would gain freedom to pursue what they enjoy, and says society's goal should shift from mandatory employment to making work optional. He is skeptical that AI will soon receive civil rights but sees possible cases for autonomous ships needing a legal nationality, and favors EU-level rather than national regulation of AI and data. On genetic engineering he says providing genetic information is never wrong in itself, while acknowledging the risk of a divided society between the genetically optimized and the unmodified, and argues political hesitation to legalize tools like CRISPR mainly prolongs the period in which only the wealthy can access them. He also describes hypothetical body and brain upgrades he would want, discusses AI ethics debates in the Bundestag around facial recognition, and closes with reflections on simulation theory and the meaning of life.https://www.youtube.com/embed/Ew4MDjRsFKc39602020-07-13T00:00:00+00:00yes https://riseof.ai/talks/what-is-the-next-big-thing-in-ai-technology-christian-guttmann/https://i.ytimg.com/vi/jz25Z9Z75no/hqdefault.jpgWhat Is the Next Big Thing in AI Technology – Christian Guttmann (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Prof. Dr. Christian Guttmann, Executive Director at the Nordic AI Institute, argues that AI is entering a phase where it will reshape how people work, receive information and interact with machines, drawing on 25 years in the field spanning IBM, big-company AI projects and academia. He predicts children growing up today may never learn to drive, will live in hyper-personalized information environments, and will see precision medicine transform healthcare within five to forty years. He revisits AI's history since Alan Turing's 1950s work and the Dartmouth researchers who founded the field, cautions against overregulation, and cites World Economic Forum estimates of a net 58 million new jobs over three years alongside a global shortage of true AI experts. Drawing on his own research into robotic soccer, multi-agent decision-making and human-AI trust, he argues companies must focus on trust and collaboration with AI, distinguishing three ways AI changes work: augmenting human judgment, automating tasks, and creating new jobs.https://www.youtube.com/embed/jz25Z9Z75no18602019-07-17T00:00:00+00:00yes https://riseof.ai/talks/what-is-the-world-s-strongest-ai-peter-bentley/https://i.ytimg.com/vi/EmBcBE9Z1F8/hqdefault.jpgWhat Is the World’s Strongest AI? – Peter Bentley (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, Peter Bentley, CTO at Braintree, argues that most of what is called AI today is "weak AI": systems good at handling variety within narrow functional limits, such as reading license plates, but unable to do anything outside that task. He contrasts this with "strong AI", which has genuine intelligence, can tackle a broader range of applications, and can learn to do things outside its current scope. Bentley tests the audience with examples including Siri, which he shows misunderstanding a live query through statistical guessing rather than understanding, Amazon Echo, the Never-Ending Language Learner, the Cyc project, and DeepMind's AlphaZero, arguing each is a form of weak AI because it manipulates symbols or statistics without real understanding, echoing the philosophical "Chinese Room" argument. He then outlines what building strong AI would require: not imitating human intelligence, growing a broad range of tasks, allowing new algorithms to emerge, and doing far more testing than today's systems receive. He closes by arguing that strong AI may eventually be needed as companions and advisors to help people manage an increasingly complex world, while cautioning that simpler, explainable systems remain preferable for most applications, especially safety-critical ones.https://www.youtube.com/embed/EmBcBE9Z1F817402018-06-10T00:00:00+00:00yes https://riseof.ai/talks/what-s-next-for-ai-florian-kuhlmann/https://i.ytimg.com/vi/VRgEXqzSgS8/hqdefault.jpgWhat’s Next for AI – Florian Kuhlmann (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Florian Kuhlmann, CTO and founder of Leverton, argues that today's narrow AI needs to take 'baby steps' toward more general capabilities before it can handle tasks that require reasoning and context. He describes Leverton's growth from two people to 90 across four offices, extracting information from legal and corporate documents with deep learning models trained daily in production. Using a hypothetical example of identifying twin brothers from a photo, and a real Leverton case of a two-column document with broken indentation, he shows that current deep learning excels only at single, narrow tasks and cannot combine visual, textual and semantic information to resolve ambiguity without heavy manual heuristics. He points to multitask learning, multimodal learning and differentiable programming as research directions that might narrow the gap toward artificial general intelligence, while stressing that businesses cannot wait for that goal. In the Q&A he discusses how Leverton stores extracted knowledge and says full natural-language understanding by machines remains far off.https://www.youtube.com/embed/VRgEXqzSgS89602019-07-20T00:00:00+00:00yes https://riseof.ai/talks/when-robots-rule-the-earth-the-age-of-em-robin-hanson/https://i.ytimg.com/vi/Gf1UfVCDKUI/hqdefault.jpgWhen Robots Rule the Earth: The Age of Em – Robin Hanson (Rise of AI Virtual Chat 2020)At a Rise of AI Virtual Chat in 2020, economist Robin Hanson discusses his book The Age of Em with host Fabian Westerheide. Hanson explains that the book takes one standard futurist assumption, that individual brains can be scanned and modeled cell by cell into a working emulation, and works out its social and economic consequences in detail rather than debating whether the technology is likely. He argues that a competitive emulation economy would select scans of only the few hundred best humans, make billions of copies of them, and push wages down to subsistence level, while the original biological humans who start out owning the capital remain comparatively rich as the economy doubles roughly every month. Hanson describes how emulations would concentrate into a few very dense cities, form status classes based on running speed, face limited career lengths despite being technically immortal, and likely gain broad practical autonomy because humans running a thousand times slower cannot supervise them closely. He also addresses opposition to the technology, sex and reproduction among emulations, and questions comparing his scenario to AI and to science-fiction depictions of uploaded minds.https://www.youtube.com/embed/Gf1UfVCDKUI37802020-06-29T00:00:00+00:00yes https://riseof.ai/talks/who-likes-pink-shirts-leveraging-customer-feedback-in-personalized-com/https://i.ytimg.com/vi/Rzf82y3oZpc/hqdefault.jpgWho Likes Pink Shirts? Leveraging Customer Feedback in Personalized Commerce – Dominique Ziegelmayer (Rise of AI Conference 2018)At Rise of AI 2018 in Berlin, Dominique Ziegelmayer, Director Product & Technology at Trusted Shops, argues today's personalized shopping is mostly superficial, using an online shirt purchase where a retailer asked for gender but kept showing colors already rejected by clicks. Ziegelmayer proposes three hypotheses about retail's future: stores will know shoppers' personal details before they arrive despite privacy laws, since retailers already try to infer demographics from behavior; machines will generate products tailored to individual preference rather than just help customers search for one; and human vendors will be replaced by AI that has read every product sheet and review and can ask a few clarifying questions instead. Present-day evidence includes Google Duplex, an early kiosk piloted at Media Markt, and facial recognition linked to emotion detection seen at trade shows. Ziegelmayer then presents Trusted Shops' own approach: deriving approximate demographic signals from customer feedback text through author profiling rather than mandatory profile questions, classifying review text to learn which product aspects customers like or dislike, and using progressive chatbot-style follow-up questions to turn vague feedback like "everything was perfect" into specific, actionable detail. The core argument is that structured feedback, not just click data, makes real personalization possible.https://www.youtube.com/embed/Rzf82y3oZpc12002018-06-10T00:00:00+00:00yes https://riseof.ai/talks/why-the-future-of-ai-is-feminist-eva-gengler/https://i.ytimg.com/vi/738Oysj5lrk/hqdefault.jpgWhy the Future of AI Is Feminist – Eva Gengler (Rise of AI Conference 2025)At Rise of AI 2025 in Berlin, Eva Gengler, co-founder of the feminist AI community, argues that today's AI is not feminist and that it must become so to avoid reinforcing existing power structures. She researches the intersection of AI and power, focusing on regulation and governance. She presents examples of bias, including AI-generated images of the Bavarian parliament that showed no women despite the body being 27 percent female, the Apple Card giving some women only 5 percent of their spouse's credit limit, an Amazon recruiting AI that automatically downgraded women, and her own study of text-to-image systems finding only 21 percent of generated people were women, dropping to 6-12 percent for 'powerful' prompts. She also cites AI used for oppression, including hijab-compliance surveillance in Iran and deepfake pornography targeting women over 90 percent of the time. Gengler presents a framework linking patriarchal, neocolonial and capitalist political context, organizational power imbalances, biased data, resource-constrained design and an automating purpose to biased AI outcomes, and proposes feminist, intersectional interventions at each stage, including diversity committees, better AI governance, and regulation, while stressing that developers alone lack the power to fix this and decision-makers must take responsibility.https://www.youtube.com/embed/738Oysj5lrk18002025-05-21T00:00:00+00:00yes https://riseof.ai/talks/winni-a-penguin-guiding-employees-into-the-ai-future-j-rgen-brinkmann/https://i.ytimg.com/vi/GcnqeztZLaU/hqdefault.jpgWINNI: A Penguin Guiding Employees into the AI Future – Jürgen Brinkmann, Eileen Neumann (Rise of AI Conference 2025)At Rise of AI 2025 in Berlin, Jürgen Brinkmann, co-lead of the AI Center of Excellence at Windmöller & Hölscher (W&H), and Eileen Neumann of SVA System Vertrieb Alexander present WINNI, a penguin-branded AI assistant W&H built to help ordinary employees, not just engineers, adopt AI at work. Brinkmann describes W&H as a 150-year-old German machine-building company facing growing complexity from regulation, IT sprawl and dense process documentation that employees struggle to use. His team built a multi-agent system that translates complex process data, including JSON-based process diagrams, into plain answers, but found employees still avoided tools branded around GPT because they did not understand or trust it. Their answer was WINNI, a young, imperfect penguin that lives inside Microsoft Teams, never criticizes users for asking the same question repeatedly, and became something employees say they love rather than merely use. Neumann then explains that although WINNI does not qualify as high-risk under the EU AI Act, W&H still applies AI governance practices she calls LLMOps, covering prompt and context versioning, model comparison, hallucination detection and human oversight, supported by a dedicated governance tool.https://www.youtube.com/embed/GcnqeztZLaU14402025-05-21T00:00:00+00:00yes https://riseof.ai/talks/world-after-capital-albert-wenger/https://i.ytimg.com/vi/JGzjXu5pqAg/hqdefault.jpgWorld After Capital – Albert Wenger (Rise of AI Conference 2019)At Rise of AI 2019 in Berlin, Albert Wenger, Managing Partner at Union Square Ventures, argues that the central question for the age of AI is not information but attention: what humans choose to pay attention to. He opens with CO2 levels reaching 415 parts per million and argues society fails to attend to climate change because market prices do not exist for the most important problems, such as an individual's purpose in life, planetary defense against asteroids, or preventing climate change, while advertising-driven attention has a clear price and is therefore over-allocated. He traces how the scarce resource shifted historically from food (foraging) to land (agriculture) to capital (industrial age), arguing markets allocate capital well but fail at allocating attention. His core proposal is that AI should be used to free human attention from what he calls the job loop, the cycle of selling labor to buy goods, rather than to capture more attention for advertising. He closes with three proposals: universal basic income for economic freedom, informational freedom through open APIs to platforms, and individual mindfulness practice, and points to his ongoing open book project, World After Capital.https://www.youtube.com/embed/JGzjXu5pqAg12002019-07-03T00:00:00+00:00yes