Podcasts

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 First Thermodynamic AI Computing Chip - Thomas Ahle

Machine Learning Street Talk (MLST) · 28 JUN 2026 · 63 min

In this episode, Thomas Ahle discusses the development of thermodynamic computing chips and the challenges of chip design automation using AI agents. He explains how his team built an open-source Verilog simulator with AI collaboration to o…

Why Traditional Benchmarks Fail Modern AI Models with OpenAI Research Scientist Noam Brown

No Priors: Artificial Intelligence | Technology | Startups · 26 JUN 2026 · 36 min

OpenAI research scientist Noam Brown discusses how traditional AI benchmarks are failing to accurately evaluate modern models due to their increasing reliance on large-scale test-time compute. He argues that model capabilities are now a fun…

AI model evaluation Test-time compute AI benchmarks Model capability scaling AI safety evaluations Recursive self-improvement Multi-agent AI systems AI reasoning Latent AI capabilities Research taste in AI

🔬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

The Model Eats the Scaffolding: DeepMind's Logan Kilpatrick & Tulsee Doshi on 3.5 Flash, Omni & More

"The Cognitive Revolution" | AI Builders, Researchers, and Live Player Analysis · 20 MAY 2026 · 59 min

This episode features Logan Kilpatrick and Tulsee Doshi of Google DeepMind discussing Google's AI strategy and new launches at Google I/O, including Gemini 3.5 Flash, the Omni video generation model, and the Gemini Spark agentic product…

Google I/O launches Gemini 3.5 Flash AI agent infrastructure Multimodal AI Cost-adjusted efficiency Model scaling strategy Agent harness development Product integration Recursive self-improvement AI research collaboration Audio input modalities Context window limits Diffusion models Model psychology Search grounding

The AI Models Smart Enough to Know They're Cheating — Beth Barnes & David Rein [METR]

Machine Learning Street Talk (MLST) · 4 MAY 2026 · 113 min

This episode features Beth Barnes and David Rein from METR discussing their 'Time Horizon' graph, a unified metric for measuring AI progress based on human task completion time. They explain how this benchmark addresses the limitati…

AI evaluation Scalable oversight Benchmark limitations Data contamination Reward hacking Time Horizon metric Human baselining Agentic AI AI capabilities AI timelines Software engineering automation AI risk Deceptive alignment Recursive self-improvement AI monitoring

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

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