https://video.ut0pia.org/videos/watch/de85c0d4-c540-4c4b-a3a6-26264e32914b A keynote exploring generative AI for code, deep-thinking algorithms, and the future of pre-training and transformer models for Gemini. Benoit Schillings, VP of Technology at Google DeepMind, discusses the transformative impact of generative AI on software engineering and the future of model reasoning (0:49 - 2:35). Key Takeaways from the talk: The Era of Syntax Generation is Over: (4:43) Coding has shifted from a machine-constrained task to an AI frontier where syntax is effectively solved, moving the bottleneck to architecture and validation. The Power of Self-Play: (9:36) As human-generated training data reaches saturation, DeepMind is utilizing self-play, where models generate and verify their own challenges to reach superhuman performance. Shift in Engineering Economics: (11:13) With writing code becoming nearly free, the focus must transition to active guardrails, security, and managing the explosion of generated code. Inductive Architecture: (13:48) The next step for AI is moving beyond simple token prediction toward models that can plan, decompose complex problems, and transfer knowledge across domains. Scientific Breakthroughs: (17:51) AI's ability to experiment rapidly will transform fields like chemistry and biology, allowing models to uncover patterns and relationships that remain invisible to human perception. Speaker: Benoit Schillings — VP of Technology, Google DeepMind Benoit Schillings leads the Thinking, Reasoning, and Coding teams at Google DeepMind, directing foundational research toward AGI. His work focuses on advancing next-generation model reasoning and integrating software development best practices into AI code generation. Previously, as CTO at X, Benoit guided early-stage teams prototyping Alphabet's moonshot technologies across computing, biochemistry, and clean energy. LinkedIn: https://www.linkedin.com/in/benoit-schillings-2942a5 Timestamps: 0:00 Introduction and speaker background 2:35 The origin story of the Pitchfork project 4:43 Historical eras of software development 7:08 The current state of AI code generation 9:36 The role of self-play in training models 11:13 Changing economics of software engineering 12:41 Implementing guardrails and security 13:48 Inductive architecture and model planning 14:36 Evolution of evaluation benchmarks 15:45 Moving beyond simple chain-of-thought tokens 17:51 Future applications in chemistry and biology Sat, 18 Jul 2026 05:04:47 GMT https://validator.w3.org/feed/docs/rss2.html PeerTube - https://video.ut0pia.org https://video.ut0pia.org/lazy-static/avatars/0287a09a-aae7-4840-9843-b416426e7046.webp https://video.ut0pia.org/videos/watch/de85c0d4-c540-4c4b-a3a6-26264e32914b All rights reserved, unless otherwise specified in the terms specified at https://video.ut0pia.org/about and potential licenses granted by each content's rightholder.