1.WHAT DID META AI ‘S NEURAL THEOREM DID?

The team’s meta AI neural theorem prover has completed five times more IMO problems than any other AI system before it, totaling ten. Regarding miniF2F, a popular math test, the AI model outperformed the state of the art by 20% and exceeded Metamath by 10%.The team’s HyperTree Proof Search (HTPS) approach learns to generalize from a dataset of correct mathematical evidence to completely new challenges.

2.WHICH IS PROVED BY NEURAL THEOREM?
A neural theorem proved that in order to behave like a human, we must associate a “state” with our existing (incomplete) understanding of the problem. The “current state” of the (unfinished) proof is shown as a node in the graph and each subsequent step is an edge. This allows us to visualize the entire proof. The Exam Assistant uses a deductive reasoning process to make this method viable.

Finally, the proposed method outperforms the current published state-of-the-art in terms of minif2f validation set accuracy by 20% and solves 10 unsolved IMO problems so far. The team hopes their work will help the community build on their work, allowing us all to progress even faster in this fascinating field.

3.HOW IS THE PRESENT SITUATION OF THE AI?
The scientific world has long recognized that proving mathematical theorems is an essential first step in the development of AI. To prove the truth or falsehood of a conjecture, it is necessary to use symbolic thought and sort through an unlimited number of alternatives. The state of the art of AI today is to create machines that can “solve at once” or find a complete answer.