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wisdomHunt: post #598 — TG.ME

wisdomHunt@wisdomHunter · 509 subscribers Open in TelegramOpen

Darmonim

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July 12, 2026 894 11 7

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Ironically, very much applies to AI field itself:) 259·Aug 19 Terence Tao: Mathematics in the Age of AI (August 17, 2026) Tao's essay based on his ICM 2026 lecture. Instead of arguing about whether AI can do research math, he conditions on the assumption that it will, and asks a different question: what do mathematicians actually value? Key ideas: 1. A second foundational crisis. 1900-1930 forced math to make its foundations explicit (set theory, formal proof). AI will force us to make our values explicit: what counts as a contribution, what we reward, who gets credit. 2. Goodhart's law hits math. Historically, all goals of mathematics (solving problems, building theory, training students, community) were correlated, so "solve open problems" worked as a proxy for everything else. AI breaks this: it optimizes for the appearance of success, and the AI industry is financially rewarded for exactly the benchmarkable metrics we used as proxies. Over-optimize one goal and the goals diverge. 3. The problem-solving pipeline is 5 stages, not 1. Generation → verification → exposition → community acceptance → canonicalization (getting into the textbooks). We only ever made the first stage explicit. AI accelerates stage 1 massively, barely touches stage 5, which Tao calls the most valuable part. Fun point: AI training data is the output of canonicalization. 4. Proof scarcity → proof abundance. Journals, priority norms, hiring, prizes were all designed for scarcity. Expect "proof indigestion": verified proofs nobody understands, correct results nobody has refereed. This is already happening on the Erdős problems database. 5. Exposition can be over-optimized too. Human proofs have "natural friction" where the author struggled, and that friction teaches you where to pay attention. AI-polished proofs sand it away, making texts easy to read but hard to learn from. He shows a Bourgain page he annotated in frustration as a grad student. His rule of thumb: if the authors can't give a clear expert-level talk on their result, it shouldn't be published. A verified proof no human can explain is incomplete. Also cites the First Proof project: 7 of 10 novel research problems got an essentially correct AI solution at $10-100s of compute per problem. @abdumalik_abdukayumov 242·Aug 19

Technology & Islam Many people tend to see technology and Islam as separate things. Muslims are often seen as more spiritually inclined, and even techno-averse. The history too backs this up on the surface, like the Ottomans effectively blocking the printing press for around 300 years. I had this same unconscious view, until something clicked: You see, in the Qur'an, reading, writing, and books are praised heavily. God emphasizes giving humans the ability to write with a pen. Now think about it - pen, book, writing, and reading - these are technology and technical skills. Meaning Islam actually encourages Muslims to engage with technology. Early Muslims lived this out too. Historically, they were the ones who made the mass production of paper a reality, enabling mass education, which directly led to the Islamic Golden Age. Now, what remains is to keep the same spirit. p.s. this view is somehow rewiring how I approach my work - making AI much closer to my beliefs. 399·Aug 15

Universities need reform What I am realizing is - I am almost finishing my master’s and I didn’t attend almost any course for more than its beginning 1-2 weeks - for both bachelor’s and master’s. This was made possible thanks to recorded lectures and AI chatbots. So my university experience says - something should change in education system. You don’t necessarily have to sit in the lectures. At the end of the day, learning is about students making sense of the content, not teachers pounding in their ears. That making sense is much better served if the student can pause the lecture, ask his questions, do more exercises, and think together with mentors. This would also give more time for lecturers to actually do more research rather than repeating the same thing again and again. This would be win-win case for both sides. In any case, presence of AI should rewire the education system and whoever does it first reaps the biggest harvest. I found this interesting article that delves deeper into this topic. 588·Aug 8

Are you guys kidding? Moonshot - the ones that kneeled down both OpenAI and Anthropic open-sourcing 2.8 trillion model. 676·Aug 4

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wisdomHunt: post #598 — TG.ME