Damon Hill
1996 Formula 1 World Champion | 22x Grand Prix Winner | Williams Racing Official Ambassador | Expert on Resilience & High-Pressure Performance
AI & Robotics Professor, UC Berkeley | Head of LLM, Amazon AGI | Co-Founder, Covariant | Pioneer of Deep Learning for Robotics
Pieter Abbeel helped invent the AI that powers today's robots, image generators, and language models — and now leads LLM development at Amazon AGI. A UC Berkeley professor whose students co-founded OpenAI, Perplexity, and Physical Intelligence, he is one of the most consequential figures in modern AI. His keynotes give senior leaders the scientific grounding and strategic clarity to act decisively in an era defined by machine intelligence.
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Pieter Abbeel is one of the world’s foremost authorities on artificial intelligence and robotics — a researcher, educator, and serial entrepreneur whose work sits at the very foundation of technologies reshaping how machines learn, move, and reason. Professor at UC Berkeley, Director of the Berkeley Robot Learning Lab, and Co-Director of the Berkeley AI Research (BAIR) Lab, Abbeel has spent two decades pushing the frontier of what intelligent systems can do — and building companies that bring those advances into the real world.
AI speaker Pieter Abbeel is best known for pioneering deep learning for robotics, co-developing diffusion models — the technology now at the heart of today’s image and video generation systems — and producing foundational reinforcement learning algorithms including TRPO and SAC, which underpin modern humanoid locomotion and are key components in the RLHF tuning methods that power today’s large language models. His lab at Berkeley has generated over 300 publications and more than 100,000 citations, making it one of the most influential AI research groups in the world. He has received the ACM Prize in Computing, the PECASE, IEEE Fellow status, and has been named among MIT Technology Review’s TR35 top innovators.
As a founder, Abbeel has built companies that define entire categories. Gradescope, co-founded in 2014, brought AI-assisted grading to over 1,000 universities before being acquired by Turnitin in 2018. Covariant, co-founded in 2017, built robotics foundation models enabling robots to see, learn, and adapt in live warehouse and factory environments — capabilities far beyond the pre-programmed motions of traditional industrial robots. In 2024, Amazon acquired Covariant’s technology and team, and Abbeel joined as an Amazon Scholar co-leading the Frontier AI and Robotics (FAR) lab. In December 2025, he was appointed to lead Amazon’s large language model efforts within its AGI organization — one of the most consequential AI leadership roles in the industry.
Perhaps Abbeel’s most remarkable contribution is the generation of founders he has trained. His PhD students and postdocs have gone on to co-found OpenAI (John Schulman), Perplexity (Aravind Srinivas), Physical Intelligence (Chelsea Finn and Sergey Levine), Ideogram (Jonathan Ho), and Evolutionary Scale (Roshan Rao), among many others. His online AI courses have reached over 100,000 students through edX, and his Deep RL and Deep Unsupervised Learning materials are standard references for researchers worldwide. He is also the founding investment partner at AIX Ventures, with a portfolio that includes Perplexity, Cohere, Weights & Biases, and Wayve, and hosts The Robot Brains podcast, where he explores the frontiers of AI with the field’s leading pioneers.
As a speaker, Pieter Abbeel brings a rare combination: the depth of a world-class researcher, the experience of a hands-on builder, and the clarity of someone who has taught complex ideas to tens of thousands of students. Senior executive audiences book him to understand where AI and robotics are truly headed — not the hype, but the science — and what it means for their organizations, their strategies, and the decisions they need to make now. His sessions on generative AI, humanoid robotics, reinforcement learning, and AI strategy consistently rank among the highest-rated at the global events where he appears.
The past decade of AI progress has been extraordinary — but the next decade will be transformative in an entirely different way. Abbeel maps the trajectory from today's large language models and generative AI to the emerging frontier of physical AI: robots and autonomous systems that can perceive, reason, and act in the real world. Drawing on his research at Berkeley and his work building Covariant and Amazon's Frontier AI and Robotics lab, he gives executives a grounded, science-based view of where AI capabilities are heading and what it means for industries built on physical labor, logistics, and manufacturing.
Generative AI is reshaping creative work, software development, scientific research, and enterprise operations — and diffusion models, a technology Abbeel helped pioneer, are at its core. This keynote demystifies the science behind today's most powerful AI systems, explains what these models can and cannot do, and translates that understanding into a strategic framework executives can use immediately. Abbeel cuts through the noise to help senior leaders build realistic roadmaps for AI adoption that are grounded in how the technology actually works.
For decades, industrial robots have been powerful but brittle — capable only of tasks they were explicitly programmed to perform. That era is ending. Abbeel explores the shift to robots that learn from demonstration, adapt to new environments, and improve with experience — the same shift that transformed software AI and is now coming to the physical world. From warehouse automation to surgical robotics to humanoid machines, he traces the implications of this transition for operations, workforce strategy, and competitive advantage across industries.
AI is no longer a technology question — it is a leadership question. In this keynote designed specifically for executive and board audiences, Abbeel translates cutting-edge AI research into actionable strategic frameworks: how to assess AI opportunities and risks, how to build internal AI capabilities versus partner externally, how to govern AI responsibly, and how to lead organizations through the cultural and operational changes that genuine AI adoption requires. Based on his experience as a researcher, founder, and faculty director of executive AI programs at UC Berkeley, this session gives leaders the confidence to make high-stakes AI decisions with clarity.
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