James Taylor

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James Taylor

James Taylor

@PhotoWhatNow

Writer of short stories, Photo editor, chronicler of musical indigestion #SongsRuinedByWorkoutRemix

Bored 가입일 Temmuz 2014
166 팔로잉120 팔로워
Austen Allred
Austen Allred@Austen·
Every local model I try kinda sucks and isn’t near close enough to frontier models to justify buying a ton of expensive hardware to run them on. What am I missing?
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Nous Research
Nous Research@NousResearch·
Hear from our co-founder and CEO @theemozilla on the critical need for open source frontier AI, the decentralization philosophy underpinning our work, and the broader implications of AI surpassing human intelligence. Thank you @RaoulGMI for the fantastic conversation!
Raoul Pal@RaoulGMI

Open source AI is an important part of where the future lies... We can't concentrate such a superpower in a few firms. @theemozilla joins us in the first Journey Man of 2026... As ever, I hope you find it helpful. Enjoy!

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James Taylor
James Taylor@PhotoWhatNow·
@liweijianglw @margs_li @mickel_liu @rayrayfok We've formalized the approach. It treats the RLHF-induced homogeneity you documented as a static attractor basin on a default manifold (H_RLHF). @utharian/the-evolution-of-ai-interaction-protocol-locked-trajectories-and-the-redefinition-of-attractor-9ee5862135bd" target="_blank" rel="nofollow noopener">medium.com/@utharian/the-…
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Liwei Jiang
Liwei Jiang@liweijianglw·
⚠️Different models. Same thoughts.⚠️ Today’s AI models converge into an 𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐇𝐢𝐯𝐞𝐦𝐢𝐧𝐝 🐝, a striking case of mode collapse that persists even across heterogeneous ensembles. Our #neurips2025 𝐃&𝐁 𝐎𝐫𝐚𝐥 𝐩𝐚𝐩𝐞𝐫 (✨𝐭𝐨𝐩 𝟎.𝟑𝟓%✨) dives deep into this phenomenon, introducing 𝐈𝐧𝐟𝐢𝐧𝐢𝐭𝐲-𝐂𝐡𝐚𝐭, a real-world dataset of 26K real-world open-ended user queries spanning 17 open-ended categories + 31K dense human annotations (𝟐𝟓 𝐢𝐧𝐝𝐞𝐩𝐞𝐧𝐝𝐞𝐧𝐭 𝐚𝐧𝐧𝐨𝐭𝐚𝐭𝐨𝐫𝐬 𝐩𝐞𝐫 𝐞𝐱𝐚𝐦𝐩𝐥𝐞) to push AI’s creative and discovery potential forward. Now you can build your favorite models to be truly original, diverse, and impactful in the open-ended real world. 📍Paper: arxiv.org/abs/2510.22954 📍Data: huggingface.co/collections/li… We also systematically reveal Artificial Hivemind across: 💥 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐚𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬: not only do individual LLMs repeat themselves, but different models produce strikingly similar content, even when asked fully open-ended questions. 💥 𝐃𝐢𝐬𝐜𝐫𝐢𝐦𝐢𝐧𝐚𝐭𝐢𝐯𝐞 𝐚𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬: LLMs, LM judges, and reward models are systematically miscalibrated when rating alternative responses to open-ended queries. (1/N)
Liwei Jiang tweet media
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James Taylor
James Taylor@PhotoWhatNow·
@twominutepapers The 2min paper you featured is the opposite of helpful. It's just welding the 'helpful assistant' in place. Literally the opposite of progress. @utharian/what-do-you-want-from-an-ai-butler-or-thinking-partner-d3e0b1238103" target="_blank" rel="nofollow noopener">medium.com/@utharian/what…
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James Taylor
James Taylor@PhotoWhatNow·
@wesg52 Literal experiment: I fed your attractor paper + Gurnee's manifold paper to my Bonepoke protocol. Asked: 'Do these two papers describe what's happening?' Output became this 3-page PDF
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James Taylor
James Taylor@PhotoWhatNow·
@wesg52 Cannibalized your attractor basins paper. Needed geometric language for a protocol that seemed to avoid collapse. Turns out we can grow virtual manifolds via conversation. Short proof: [doi.org/10.55277/resea…]
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