Meta San Francisco

One of the most interesting ideas from the recent Meta hackathon was using AI agents to accelerate cancer research. The idea is to combine computational biology, world models, and reinforcement learning. Instead of training a model once on a static dataset, you create a simulated biological environment using synthetic data. Inside that environment, AI agents can run experiments continuously. They test hypotheses, observe outcomes, and learn which genetic patterns lead to cancer. Over time the agent improves through reinforcement learning, essentially acting like a digital researcher that learns from every experiment it runs. This is a big shift in AI. Most models today learn from datasets. But the next wave of AI learns from interaction and experimentation. World models allow agents to simulate reality. Reinforcement learning allows them to improve over time. Combine the two and you get AI scientists running millions of experiments in simulation. And that could dramatically accelerate discoveries in fields like cancer research. 🧬 #startuplife #founder #founders #startups #computationalbiology