Gemini Deep Think: Redefining the Future of Scientific Research

Google DeepMind presents two papers detailing how Gemini Deep Think mode, powered by an agentic math research system codenamed Aletheia, is solving professional research-level problems across mathematics, physics, and computer science. In pure mathematics, the system achieved up to 90% on IMO-ProofBench Advanced, autonomously solved four open problems from Bloom’s Erdos Conjectures database, and produced multiple research papers with varying levels of AI autonomy. In computer science and physics, Deep Think helped resolve 18 research problems including a decade-old conjecture in online submodular optimization, classic algorithmic problems like Max-Cut by bridging disparate mathematical fields, and gravitational radiation calculations for cosmic strings. The authors propose a taxonomy for classifying AI contributions to mathematical research by significance and degree of autonomy, and emphasize the “Advisor” collaboration model where humans guide AI through iterative proof cycles.

Source: Gemini Deep Think: Redefining the Future of Scientific Research