@CsabaSzepesvari
"If there is not folly in the world, then the world itself is folly. You must understand that mistakes are not always regrets." - Paul Tobin, Bandette🤠
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The essay’s author shares personal reflections on a growing disconnect between scientific rigor, professional recognition and organizational rewards.
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The incoming professor says they're recruiting PhD students and postdocs for fall 2027 in reinforcement learning and deep learning.
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A co-instructor says seven exams account for 85% of the grade, with in-person discussion assessments making up 15%.
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A user puts their “P(doom)” at 1e-5 and calls themself an optimist.
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A user says they can choose only between “not willing” and “not not willing,” with no grades or shades of gray.
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A would-be attendee said they couldn’t get into the Courant professor’s talk despite arriving on time. Those seated had arrived 20 minutes early, they said.
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A commenter argues that there’s no single way to measure how good an explanation is: the reader and their tastes matter.
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Citing news from UCLA Math Circle, a post says Aayush Bathija and Prince Rohatgi worked with postdoc Daniel Soskin to solve a problem Fields Medalist June Huh had worked on without solving.
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The MathAdv team says the reverse—solving an equivalent reformulation but not its original—never occurred in its paired test. It calls this evidence of brittleness, not proof of memorization.
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Posts say 25 Fields Medal winners signed a declaration warning of a mismatch between AI companies and mathematics. Supporters stress understanding and scientific communities; critics say AI proofs can still yield insights.
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The host’s September 9 announcement said the discussion would examine what would count as a verified solution and what such a result could mean for artificial general intelligence.
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One post connects the question of knowledge’s usefulness to the step-by-step automation of knowledge production.
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The quoted writer says GPT Astra has never given them a bug-free result on the first try and calls building projects with it “painful.”
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Anthropic says its model produced the first end-to-end computer-checked version of the theorem.
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Yale assistant professor posts arXiv paper and thread testing implicit tensor product representations in neural networks.
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Initiative supplies frontier models to scientists and engineers to speed discovery.
