Key Features
Tech Stack
*Reality checks:* * Best vision models: 28.8% accuracy on tasks requiring physics/time/causality * FDA approvals for generative AI in clinical use: Zero * 1000x gap in data efficiency between AI and human brains * 10 years of daily financial data = 2,500 observations (way too small for transformers)
*Actual breakthroughs:* * Brain-computer interfaces detecting subconscious error signals (90% to 99% accuracy) * Apple Watch pulse geometry predicting heart disease better than cholesterol * Multimodal fusion eliminating the need for 10,000 human labels per robot task * Dynamic portfolios spontaneously switching hedging instruments during COVID
*Episode list:*
1. *Society's Fragile Equilibrium* - Why "good enough" AI at scale is more disruptive than superintelligence (AGEI vs AGI) 2. *The Evaluation Crisis* - Why we're testing AI wrong (the infant morality study, Clever Hans effect) 3. *The Reasoning Revolution* - How o1/o3 actually think, mode collapse, the artificial hivemind problem 4. *Engineering Creative AI* - DALL-E training 23x faster with one token, world models, IP questions 5. *AI Transforms Scientific Discovery* - Dolphin communication, ground squirrels to heart treatments, virtual cells 6. *Foundation Models for Brain and Body* - Biological age gap from wearables, BCI error detection, SSL for neural data 7. *Computer Vision's Journey* - AI vision is solved, AI reasoning is not (28.8% reality check) 8. *Robots That Learn Without Humans* - Zero-shot robotics training via multimodal fusion 9. *The Autonomous Agent Revolution* - Reward hacking everywhere, why rigid multi-agent systems fail 10. *Generative AI in Finance* - Four pitfalls that break standard AI, task-driven training solutions 11. *AI as Time Machine for Science* - Years to days, but zero FDA approvals (the central tension)
*Sources:* NeurIPS 2025 workshops and invited talks (Yejin Choi, Melanie Mitchell, Zeynep Tufekci, etc.)
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