@rohanpaul_ai: “I do see more and more mass-produced mathematics at scale." ~ Terry Tao AI makes this scalable. Will turns proof-writi…
Summary
Terry Tao remarks on AI enabling mass-produced mathematics at scale, turning proof-writing into a searchable problem that generates thousands of mini-lemmas and filters them with cheap checkers.
View Cached Full Text
Cached at: 05/25/26, 06:42 PM
“I do see more and more mass-produced mathematics at scale.“ ~ Terry Tao
AI makes this scalable. Will turns proof-writing into search problem: it generates 1000s of mini-lemmas from a goal, then cheap checkers kill most and keep the few that works https://t.co/BHb5jdBpXy
Similar Articles
How Terry Tao became an evangelist for AI in math
Terry Tao, a renowned mathematician, discusses his evolving views on artificial intelligence in mathematics and his advocacy for large-scale collaborations and computer verification of proofs.
@rohanpaul_ai: Terence Tao summarized how AI is massively accelerating math career and math research. "In math, you previously had to …
Terence Tao discusses how AI is dramatically accelerating math research, reducing the years of education needed to contribute to the frontier.
It's great to see how automated theorem proving is moving from a niche tool to solving real math problems
Automated theorem proving is evolving from niche tools like Lean 4 into systems aided by machine learning that can solve real mathematical problems, such as verifying a counterexample to an Erdős conjecture.
@KempeLab: Automated AI theorem proving has moved the frontier: The holy grail is not an AI that can produce an endless pile of tr…
This paper introduces a metric for the intrinsic interestingness of mathematical theorems and trains a 27B model to predict proof difficulty, enabling the generation of more interesting and novel mathematics with reduced overlap with existing libraries.
Terence Tao on “prematurely solving [a maths] problem by purely AI-powered methods”
Terence Tao discusses concerns about solving mathematical problems prematurely using purely AI-powered methods, a sentiment the author believes also applies to programming.