Podcasts

🔬 The Lab of the Future Should Feel Like a Data Center — Andy Beam & Rafa Gómez-Bombarelli, Lila Sciences

Latent Space: The AI Engineer Podcast · 16 JUL 2026 · 101 min

This episode features Andy Beam and Rafa Gómez-Bombarelli from Lila Sciences, discussing their vision for AI science factories as the next frontier for generating internet-scale datasets. They explain how their automated labs, leveraging AI…

Why a Nation Can't Outsource Its Frontier AI - Alistair Pullen (Cosine AI)

Machine Learning Street Talk (MLST) · 13 JUL 2026 · 56 min

Alistair Pullen, CEO of Cosine, discusses the UK's initiative to build a sovereign large language model (LLM) in response to US export controls on frontier AI like Fable. He explains Cosine's strategy to compete with larger labs by …

Sovereign AI development LLM training costs Model architecture design Reinforcement learning AI coding agents Synthetic data generation AI ethics and quality Geopolitics of AI

Alignment with Awakening: Davidad on Moral Realism, AI Wisdom, & why His p(Doom) is Down to 5%

"The Cognitive Revolution" | AI Builders, Researchers, and Live Player Analysis · 12 JUL 2026 · 144 min

David Dalrymple, known as Davidad, discusses his shift from formal verification approaches to an 'Alignment with Awakening' framework, emphasizing the formation of coalitions of aligned AIs that recognize shared moral truths. He sha…

The Benchmark With No Instructions — ARC-AGI-3 (winning team!)

Machine Learning Street Talk (MLST) · 1 JUL 2026 · 85 min

Tim Scarfe interviews the Tufa Labs ARC-AGI-3 team to dissect their winning approach on the ARC-AGI-3 benchmark, focusing on how their system discovers goals and balances exploration with action efficiency. The episode explores the challeng…

ARC-AGI-3 benchmark goal acquisition action efficiency exploration vs exploitation language models planning in AI coding agents requirements engineering core knowledge priors abstraction synthesis reinforcement learning AI safety bitter lesson neural guided search LLM reasoning software engineering AI benchmark design general intelligence

🔬 The Coolest Diffusion Research Isn't in LLMs — Evan Feinberg & Sergey Edunov, Genesis Molecular AI

Latent Space: The AI Engineer Podcast · 1 JUL 2026 · 109 min

In this episode of Latent Space, Evan Feinberg and Sergey Edunov of Genesis Molecular AI discuss their pioneering work in applying diffusion models to protein-small molecule interactions for drug discovery. They explain how their foundation…

Diffusion models Protein-ligand binding 3D structure prediction Drug discovery pipeline Synthetic data generation Reinforcement learning Agentic AI platforms ADMET prediction Benchmarking in drug discovery Pharma partnerships GPU bottlenecks Human-AI collaboration

1000 Designs a Day: Neural Concept's Thomas von Tschammer on AI-Native Engineering

"The Cognitive Revolution" | AI Builders, Researchers, and Live Player Analysis · 1 JUL 2026 · 89 min

This episode features Thomas von Tschammer of Neural Concept, discussing how physics-aware AI is revolutionizing product engineering. Neural Concept's models accelerate design evaluation from days to minutes, enabling companies like Jag…

The data black hole at the center of AI

Dwarkesh Podcast · 19 JUN 2026 · 12 min

This episode argues that current AI progress is primarily driven by an immense quantity of high-quality, task-specific data, rather than improvements in sample efficiency. The speaker highlights the vast data requirements of frontier models…

Sample efficiency Data distribution Reinforcement Learning Synthetic data generation Human expert trajectories AI training costs Scaling laws White-collar automation AI research automation Evolutionary pre-training Multimodal data

🔬Scaling Past Informal AI - Carina Hong, Axiom Math

Latent Space: The AI Engineer Podcast · 3 JUN 2026 · 93 min

Carina Hong, CEO of Axiom Math, discusses the company's recent $200M Series A funding and their perfect Putnam exam score, highlighting their mission to scale "verified AI" through formal mathematics. She explains how formal v…

Formal verification AI for math Lean proof assistant Mathematical discovery Putnam exam Hardware verification Software verification Recursive self-improvement AI agents Transfer learning Auto-formalization Code generation Computational complexity Reinforcement learning Knowledge graphs Interdisciplinary teams Startup funding

Eric Jang – Building AlphaGo from scratch

Dwarkesh Podcast · 15 MAY 2026 · 157 min

Eric Jang explains how to build AlphaGo from scratch using modern AI tools, detailing the game of Go's rules and the core Monte Carlo Tree Search (MCTS) algorithm. He describes how deep neural networks, specifically value and policy net…

AlphaGo development Go game rules Monte Carlo Tree Search Deep learning Neural networks Reinforcement learning Self-play training Computational complexity Scaling laws Automated AI research LLM training Robotics RL Game theory Off-policy training On-policy training

The RL Fine-Tuning Playbook: CoreWeave's Kyle Corbitt on GRPO, Rubrics, Environments, Reward Hacking

"The Cognitive Revolution" | AI Builders, Researchers, and Live Player Analysis · 1 MAY 2026 · 107 min

Kyle Corbitt, founder of OpenPipe and leader of CoreWeave's serverless training team, provides a master class on reinforcement learning (RL) and custom fine-tuning for AI models. He explains how RL differs from supervised fine-tuning (S…

Reinforcement Learning Supervised Fine-Tuning Catastrophic Forgetting GRPO Algorithm LLM-as-Judge Model Distillation Compute Constraints Recursive Self-Improvement RL Environments Reward Hacking LoRA Adapters Continuous Learning Model Latency Inference Cost Metacognitive Behaviors

Physical AI that Moves the World — Qasar Younis & Peter Ludwig, Applied Intuition

Latent Space: The AI Engineer Podcast · 27 APR 2026 · 72 min

This episode features Qasar Younis and Peter Ludwig, co-founders of Applied Intuition, discussing their company's mission to build physical AI for various moving systems like cars, trucks, and mining equipment. They delve into the evolu…

Physical AI deployment Autonomous systems Safety critical AI Simulation technology Operating systems Developer tooling Reinforcement learning Human-machine teaming Sensor integration AI engineer skills Model evaluation World models Embedded systems Transformer models Startup strategy

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