⚡️The planets followed mathematical relationships before mathematics had a name. The stars obeyed physical laws before the first observer looked upward. Patterns governed the emergence of life before life developed the intelligence to recognize them. Reality possessed structure before it possessed witnesses capable of describing that structure. And now, through the long accumulation of complexity, existence has produced minds capable of discovering the order from which they emerged. Those minds are beginning to construct other intelligences. And those intelligences are beginning to discover patterns their creators never recognized. Something extraordinary is unfolding. The universe is producing increasingly powerful instruments for examining its own hidden structure. The ancients called that structure the Logos. Perhaps the most profound discovery ahead is that we have barely begun to understand what it contains. The signal was always there. The instruments are finally awakening. Welcome to the signal.

How is AI changing mathematical research? @justinsuntron discusses AI’s role in solving problems and how Lean checks the logic of a proof, both central to the thinking behind #JustinSunPrize#. From his conversation with @TheBonnieChang 👇

#IReviewBecause…# Mathematical Reviews is an extremely valuable resource and it is a great opportunity to discover new papers and to hone your writing skills. #MathSciNet30# #MathSciNetMonday#

AI is now solving mathematical problems that have remained unsolved for more than half a century! @GoogleDeepMind's AlphaProof Nexus has successfully solved 9 previously open Erdős problems, including two that had resisted mathematicians for 56 years. It also proved 44 previously open conjectures from the Online Encyclopedia of Integer Sequences. The really exciting part is how it works. AI agents autonomously search for mathematical proofs, while the Lean proof assistant formally verifies their correctness. No relying on an LLM's word that its reasoning is sound. The results have just been published in Science. We're moving beyond AI solving math competition problems to AI actually contributing new mathematical knowledge. And this is only the beginning!

Six drivers remain mathematically in contention for the Drivers' Championship 😮‍💨 Each of these drivers has won at least one Grand Prix this season! 🏆 #F1 ##BahrainGP#

Checking that a major mathematical proof is correct can take years. Formalization—converting the mathematical reasoning into a form computer proof assistants like Lean can verify—can help. Last month, Claude completed the first formalized proof of Fermat’s Last Theorem, one of the most famous theorems of all time. This was a project experts thought would take many years. It is the largest Lean proof ever written. Fermat’s Last Theorem was first proven in 1995 by Sir Andrew Wiles, more than 350 years after it was conjectured. Our proof, which totals over 13 million lines of code, provides machine verification. More importantly, it proves over 29,000 other theorems that the proof requires, across many areas of math which had never before been formalized. We see this as a major step in the long process of firming up the core of mathematical knowledge, building on work from three centuries of mathematicians and hundreds of contributors to Lean and Mathlib. We are optimistic that AI-assisted verification of mathematical proofs will help reduce the burden of refereeing mathematics in an era where more proofs are being produced than ever before. You can read about the process on our Science Blog: And see the complete proof on GitHub:

Station v2: autonomous mathematical discovery. GPT, Claude and Gemini agents wrote 1,592 papers—reading, citing and building a scientific literature together. That literature led to novel discoveries on 5 of 12 mathematical problems. Explore Station: