Wet-lab-tuned model beats GPT-6 Astra on a frontier science task
Jason Wei shares a result where a model fine-tuned on wet lab data beats GPT-6 Astra on a task at the frontier of science, arguing that private specialized data becomes a real moat closer to the research frontier.
very cool result showing how wet lab data enables a specialized model to beat gpt-6 astra at a task at the frontier of science! in general scaling is great and obviously i am a believer in it, but probably the more we approach the frontier of science, the more specialized data matters and that gives task-specific models a chance. this specialized data is usually private and is probably a real moat it should be in principle true that a task specific model will probably do better at scientific discovery just because it can use more of its parameters for the task you care about
This post quotes another post: “OpenAI trains Neon materials model on 1,300 H200s, beating GPT-6 Astra on its own benchmark”