this is why there is a massive (growing) gap between open-source and the frontier
@jxmnop
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American AI Labs Stockpile Data While China Awakens to Reality
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over the last few years ~four american AI labs have stockpiling many petabytes of Good Data. no one else has this, it costs billions of dollars once china wakes up to the reality of cold-hard Data (purchased, stockpiled, compounding), the landscape will undergo a giant shift
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Anthropic Had Mythos Internally Since February 2024
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ANTHROPIC HAD MYTHOS INTERNALLY SINCE FEB 24
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Curating AI Knowledge Through Algorithm-Driven Digests
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there are a few ways, but most of these came from friends or from my carefully cultivated algorithm in http://
scholar-inbox.com digests -
Recent ArXiv Papers Worth Following Daily
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"there's nothing interesting on arxiv these days!" – the words of an uncurious mind i have personally been blown away by the volume of interesting papers posted over the last few months, and eagerly following daily digests here are some papers i enjoyed the most: –
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Cooling H100s in Space: GPU Hardware Obsolescence Challenge
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dumb question, how do you cool a datacenter in a vacuum?
— dr. jack morris (@jxmnop) 3 novembre 2025
also H100s are already nearly obsolete oops gotta send a datacenter sysadmin astronaut out there to swap in B200s https://t.co/7efbQNwhHndumb question, how do you cool a datacenter in a vacuum? also H100s are already nearly obsolete oops gotta send a datacenter sysadmin astronaut out there to swap in B200s
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Open-source AI transparency crisis: Chinese base models audit challenges
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state of open-source AI in 2025:
– almost all new open American models are finetuned Chinese base models
– we don’t know the base models’ training data
– we have no idea how to audit or “decompile” base models who knows what could be hidden in the weights of DeepSeek -
AI Researchers Need Peer-Reviewed Publications for Credibility
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my most controversial opinion is that you shouldn’t trust anyone that calls themself an “AI researcher” but has never gotten a first author paper through peer review
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AI Adoption Consequences: From Content Platforms to AI Systems
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first AI came for stackoverflow and i did not speak out due to their unpleasant moderators then AI came for quora and i did not speak out because i never use quora then AI came for Wikipedia and i did not speak out because i did not care then AI came for AI
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AI Researchers Podcast in Montreal
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had so much fun podcasting with some other AI researchers in Montreal last week this is how McGill looks in the fall btw