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@avt_im
Unconventional academic starting something new · Bayesian decision theory · AI safety · anti-ideological · fmr. @Cornell faculty, @CambridgeMLG @ImperialMaths
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A user recommends linked Anthropic research as a grounded, quantitative and qualitative case study of that change.
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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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One user says the acknowledgments contradict the meme; a reply argues a model could try roughly 100 alternative prompts.
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Mistral says Mistral Large 4 is live via API in public preview now, with open weights due at the end of October. Reuters says the launch is part of Mistral’s push to narrow the gap with leading Chinese open-weight models.
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A respondent says their product roadmap largely grew from building infrastructure for basic research with production engineering standards.
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Josh Albrecht compares fixed LLMs to books; critics say the analogy overlooks implementation and scientific uncertainty.
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A commentator argues that assumed duties toward conscious AI make it harder to examine whether AI is conscious.
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David George’s a16z analysis argues that adoption remains shallow, citing a gap between reported AI impact and tracked metrics at S&P 500 companies.
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A poster rejects the idea that important work requires a frontier lab and 10,000-plus GPUs. He says some people he talks to think they should leave AI research because they expect end-to-end research to be automated.
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A user says reimplementing a GPU-accelerated hash table in CUDA took two days to reach state-of-the-art performance. Six months later, they put a similarly difficult project at a few hours.
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A user says they prompted Claude, went hiking for several hours and returned to a working codebase. They shared the project, compress-pdf, on GitHub and crates.io.
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One reader says the strip made them empathize with Astra and feel bad about what happened in a Minecraft run.
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A user questions the reassurance of having another agent grant permission: why should the reviewer deserve more trust than the agent doing the work?
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Another user offers a blunt self-assessment: plenty of code they're proud of, but much more they now explain away as work written “before AI.”
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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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One post connects the question of knowledge’s usefulness to the step-by-step automation of knowledge production.
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In a test pairing a 753-billion-parameter model with a 4-billion-parameter model, the team reports results 80% as accurate as the frontier model at 20x faster performance.
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Alexander Terenin states Lean bugs exploited by LLMs will be short-term.
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Independent AI commentator forecasts Claude solved Millennium Prize problem before company IPO.
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Cornell AI researcher posts quote comparing AI to social media as a revealing mirror.
