Jason Wei: Wet-Lab Data Lets Specialized Models Beat GPT-6 Astra at Frontier Science
vwxyzjn · x · 2026-09-16
Jason Wei highlights a result where a specialized model trained on wet-lab data beat GPT-6 Astra on a frontier science task. His take: scaling still works, but the closer you get to the frontier of science, the more specialized data matters — giving task-specific models an edge since more parameters serve the target task, and such private data may be a real moat. The quoted khoomeik thread frames this as building a post-training data flywheel for science ("labs that learn"), analogous to what math and coding already had.
More from AGI Musings
- Math's loudest AI skeptic Daniel Litt now expects to lose his 2030 bet — ziv_ravid · 2026-09-16
- Carissa Véliz: the question isn't how dangerous AI is, but the people building it — CarissaVeliz · 2026-09-16
- Philosopher Carissa Veliz: don't let tech executives set the AI agenda — CarissaVeliz · 2026-09-16
- STEM exodus to industry may push universities back to a pre-industrial form — begusgasper · 2026-09-16
- First large-scale 'AI in Science' report released as start of new research agenda — soumitrashukla9 · 2026-09-16
- Inside a rationalist AI-doomer meetup: questioning 'AI kills everyone' got me walked out on — StewartalsopIII · 2026-09-16