ScienceBuddy: Recursive-in-Recursive Self-Improvement for Interactive Scientific Agents
An AI that learns and improves by working alongside actual scientists
ScienceBuddy is an interactive workspace where AI agents improve themselves through direct collaboration with researchers. The system uses a two-layered learning approach: it refines how it tackles problems while simultaneously training its underlying model, turning researcher feedback into fuel for continuous improvement across tasks like literature review, hypothesis generation, and experimental design.
Most scientific AI tools are static—once deployed, they stop learning. ScienceBuddy evolves in real time as researchers use it, meaning the tool gets smarter the more it's deployed in actual labs. This could accelerate discovery by letting AI and human experts complement each other continuously rather than in one-off interactions, and by making cutting-edge AI capabilities accessible to working scientists without requiring them to retrain models themselves.