What happens when AI begins improving itself, and then turns that intelligence toward science? Richard Socher, pioneering AI researcher and CEO and co-founder of Recursive, joins Matt Turck to explore the vision behind his new book, The Eureka Machine. They discuss why scientific progress may be slowing, how large language models can learn the hidden languages of proteins and biology, and why simulations, verifiers and autonomous experiments could unlock superhuman AI capabilities. The conversation covers recursive self-improvement, AI drug discovery and cancer research, hallucination as creativity, virtual cells, self-driving laboratories, agent swarms, the AI Economist, Recursive’s plans, and the compute and data needed to build an AI scientist that never stops learning—and may eventually discover what humans cannot. (00:00) Intro: AI That Improves Itself(00:55) Why Scientific Progress Is Slowing(03:08) The Labyrinth of Human Knowledge(05:59) Can AI Put Science Back Together?(07:57) How LLMs Learn Biology and Proteins(10:56) Next-Token Prediction as a World Model(16:44) Can AI Generate Truly Original Ideas?(17:32) Simulations, Verifiers and Superhuman AI(22:18) The Path to Recursive Self-Improvement(24:49) Why AI Hallucinations Can Drive Discovery(27:42) From Reading Biology to Writing It(31:31) Can AI Accelerate Drug Discovery?(33:31) Will AI Help Cure Cancer?(38:03) AI Breakthroughs in Biology, Energy and Materials(40:19) Will Some Societies Reject AI?(45:07) Building the AI Economist(52:22) The Scientific Data Bottleneck(53:41) The Four Pillars of the Eureka Machine(55:01) Teaching AI the Rules of Reality(57:44) Simulations and Virtual Cells(1:00:40) Self-Driving Robotic Laboratories(1:02:51) Agent Swarms and Open-Ended Discovery(1:04:30) The Compute Bottleneck(1:05:44) Inside Recursive(1:07:33) What Recursive Will Build First(1:10:10) How Do We Define Intelligence?(1:11:32) How Far Can Intelligence Go?

What happens when AI begins improving itself, and then turns that intelligence toward science? Richard Socher, pioneering AI researcher and CEO and co-founder of Recursive, joins Matt Turck to explore the vision behind his new book, The Eureka Machine. They discuss why scientific progress may be slowing, how large language models can learn the hidden languages of proteins and biology, and why simulations, verifiers and autonomous experiments could unlock superhuman AI capabilities. The conversation covers recursive self-improvement, AI drug discovery and cancer research, hallucination as creativity, virtual cells, self-driving laboratories, agent swarms, the AI Economist, Recursive’s plans, and the compute and data needed to build an AI scientist that never stops learning—and may eventually discover what humans cannot. (00:00) Intro: AI That Improves Itself (00:55) Why Scientific Progress Is Slowing (03:08) The Labyrinth of Human Knowledge (05:59) Can AI Put Science Back Together? (07:57) How LLMs Learn Biology and Proteins (10:56) Next-Token Prediction as a World Model (16:44) Can AI Generate Truly Original Ideas? (17:32) Simulations, Verifiers and Superhuman AI (22:18) The Path to Recursive Self-Improvement (24:49) Why AI Hallucinations Can Drive Discovery (27:42) From Reading Biology to Writing It (31:31) Can AI Accelerate Drug Discovery? (33:31) Will AI Help Cure Cancer? (38:03) AI Breakthroughs in Biology, Energy and Materials (40:19) Will Some Societies Reject AI? (45:07) Building the AI Economist (52:22) The Scientific Data Bottleneck (53:41) The Four Pillars of the Eureka Machine (55:01) Teaching AI the Rules of Reality (57:44) Simulations and Virtual Cells (1:00:40) Self-Driving Robotic Laboratories (1:02:51) Agent Swarms and Open-Ended Discovery (1:04:30) The Compute Bottleneck (1:05:44) Inside Recursive (1:07:33) What Recursive Will Build First (1:10:10) How Do We Define Intelligence? (1:11:32) How Far Can Intelligence Go?

When AI Improves Itself | Richard Socher (Recursive)

We're joined by Sarah Catanzaro, General Partner at Amplify Partners and one of the leading investors in AI, ML, and data to talk about the startup landscape, LLMs, and more.

We're joined by Sarah Catanzaro, General Partner at Amplify Partners and one of the leading investors in AI, ML, and data to talk about the startup landscape, LLMs, and more.

Amplify Partners: AI Investing and the Startup Landscape with General Partner Sarah Catanzaro

AssemblyAI Founder & CEO, Dylan Fox joined FirstMark Managing Partner, Matt Turck for Data Driven NYC! AssemblyAI is the fastest way to build with AI for audio. With a simple API, get access to production-ready AI models to transcribe and understand speech. AssemblyAI has raised $63M+.

AssemblyAI Founder & CEO, Dylan Fox joined FirstMark Managing Partner, Matt Turck for Data Driven NYC! AssemblyAI is the fastest way to build with AI for audio. With a simple API, get access to production-ready AI models to transcribe and understand speech. AssemblyAI has raised $63M+.

AssemblyAI Founder &amp; CEO, Dylan Fox joined FirstMark Managing Partner, Matt Turck for Data Driven NYC! AssemblyAI is the fastest way to build with AI for audio. With a simple API, get access to production-ready AI models to transcribe and understand speech. AssemblyAI has raised $63M+.

Assembly AI: Generative AI for Speech Recognition with CEO Dylan Fox

William Falcon, Founder of Lightning AI joins Matt Turck for a conversation on pytorch, LLaMAs, the future of large language models, and more.

William Falcon, Founder of Lightning AI joins Matt Turck for a conversation on pytorch, LLaMAs, the future of large language models, and more.

Lightning AI: Build and Deploy AI with Pytorch with CEO William Falcon

The MAD Podcast with Matt Turck is a leading AI podcast - deeply-researched but accessible conversations with the people building the AI revolution. Guests include frontier researchers from OpenAI, Anthropic, Google DeepMind and the new wave of AI labs; founders and CTOs of breakout AI startups (Vercel, LangChain, Granola, Legora); and leading analysts such as Benedict Evans and Dylan Patel. Matt is a General Partner at FirstMark and an active early-stage investor in AI startups. New episodes weekly, with full transcripts at mattturck.com/podcast.

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The MAD Podcast: Machine Learning, AI & Data with Matt Turck

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