AI systems like AlphaProof are on the right track and will continue to improve, suggesting that the future of mathematics could be transformed by AI.

At Google DeepMind, we've been applying AI across almost every branch of science, achieving breakthroughs in areas from mathematics to life sciences, including developing AlphaProof for solving Math Olympiad problems and AlphaFold for predicting molecular structures.

If AI can develop a sense of viability for proof strategies, it could potentially collaborate with human mathematicians, enhancing the problem-solving process.

AI is expected to change mathematics significantly, with projects like AlphaProof focusing on proving conjectures and potentially leading to new interesting conjectures in the future.

AlphaProof is a system that learns to prove mathematical theorems through experience, without being told how to prove them, ensuring the correctness of its proofs.

DeepMind's work on reinforcement learning, particularly with AlphaGo and AlphaZero, has shown that algorithmic advancements can lead to substantial improvements in AI performance, often requiring far less training than traditional methods.

The difficulty of proving mathematical problems increases exponentially with the number of steps involved in the proof, making it challenging for AI systems to maintain accuracy.

Self-play mechanisms in AI, where systems play against themselves, have led to significant advancements in reinforcement learning, exemplified by systems like AlphaGo and AlphaZero.

The proofs generated by AlphaProof can be translated back into human-understandable language, allowing mathematicians to verify and understand the solutions.