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@_onionesque
Cultivated Abandon. Twitter interests: Machine learning research, applied mathematics, mathematical miscellany, ML for physics/chemistry, books.
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One poster links data companies' earnings to frontier labs' lack of access to what they call “product surface.”
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A user argues the effort would not be a months-long project and would require a large team.
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A user recalls McAllester discussing the topic in 2012–14 and praises his positive outlook.
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A user predicts more intense talk of a coming catastrophic AI event as credit-default-swap spreads get “more interesting.”
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A user welcomes the perceived change, recalling questions about whether someone 'respects language.'
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A poster says almost any Stage 4 cancer patient would find human understanding of a working cure's mechanism irrelevant.
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One post argues that the AI moment may be unusual in how it concentrates unresolved issues into worldviews.
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A user shared the statement; another criticized people they said were attacking it while defending OpenAI.
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An arXiv paper describes workflows in which a generator proposes candidates and a cheap verifier scores them.
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OpenAI says it drew on an independent mathematics advisory group’s advice about how to release the results.
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A user joked that every second word they heard in the background at an SF bar was “AI.”
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A paper on arXiv notes that connections between conformal prediction and permutation tests are already widely known in the literature.
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A researcher urges junior researchers to hone their writing and think carefully about what individual words mean and evoke in readers.
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In a sarcastic follow-up, the user jokes that AI rumor spreaders now have their own “credentialed professional community.”
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The user’s experience-based comparison includes academic labs that measure AI capabilities and risks.
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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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A user calls V4.1 “very brittle,” claiming it can see “massive gains” when AGENTS.md instructions are optimized for a particular scenario.
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Andrew Curran claims Anthropic shared the plans during pre-IPO investor meetings.
