Medicine's AI misalignment problem, through the lens of the Navier-Stokes debacle
davidjhwu · x · 2026-09-17
The author examines the Navier-Stokes Millennium Prize controversy: after learning a mathematician using Codex was close to a solution, OpenAI reportedly deployed 10,000 agents and millions of dollars of compute to brute-force a possible answer within days. The researcher alleged foul play; OpenAI said it didn't explicitly train on his chats but "cannot rule out" that de-identified data from his usage helped improve its models. The piece extends this to medicine, arguing the field faces its own AI misalignment problem around IP boundaries, data ethics, and the displacement of domain experts.
More from AGI Musings
- Preferring public sharing over feeding company proprietary training data — ShenRaphael · 2026-09-17
- panickssery: crippling AI regulation worries me more than falling behind China — panickssery · 2026-09-17
- repligate: the AI backlash targets EAs' wokeness, not superhuman intelligence itself — repligate · 2026-09-17
- Unconv AI CEO: AI doomerism is financially motivated fearmongering with no credible evidence — NaveenGRao · 2026-09-17
- Jeff Dean drops 60-minute AI engineering masterclass, from building an LLM from scratch to orchestrating 100 agents — goyalshaliniuk · 2026-09-17
- Patrick Collison: papers are trivially easy for AI models to read but walled off for humans — anshulkundaje · 2026-09-17