Scaling a protein model is what lets RL beat trial-and-error protein design
· 8 min read
Designing a protein means searching a huge space of options while each real test costs money. A popular approach is to fine-tune a big protein AI with reinforcement learning. Our lab ran a fair contest against plain trial-and-error. The AI only wins once you make the model bigger, and the win comes from giving the search a better starting point, not from the model knowing which proteins are good.