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.)