Practitioners On X
232 resources · page 2 of 8
Борис опять (@boris_again)
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Борис опять Telegram channel by Boris Tseytlin: Russian-language posts and weekly AI digests.
@BEBischof (Bryan Bischof)
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X account of Bryan Bischof: posts on evaluating LLM systems in production.
Buck Shlegeris (@bshlgrs)
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Redwood Research, led by Buck Shlegeris: AI safety research organisation working on AI control.
ARENA: AI Safety Education
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ARENA: AI safety education programme teaching technical alignment and interpretability skills.
Cameron R. Wolfe (@cwolferesearch)
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Cameron R. Wolfe's Deep (Learning) Focus newsletter explaining AI research topics in depth.
Casey Newton (@CaseyNewton)
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Casey Newton's Platformer: independent reporting on AI and social platforms.
Chris Olah (@ch402)
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Chris Olah's blog: explanatory essays on neural networks, interpretability and visualisation.
Chris Paxton (@chris_j_paxton)
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Chris Paxton's It Can Think! newsletter on robotics and AI.
LAION
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LAION site: nonprofit co-founded by Christoph Schuhmann releasing open datasets, models and tools.
@ClementDelangue (Clément Delangue)
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X account of Clément Delangue, Hugging Face CEO: posts on open-weights models and the open AI ecosystem.
Clémentine Fourrier (@clefourrier)
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Hugging Face evaluation guidebook GitHub repo by Clémentine Fourrier: practical and theoretical guidance on LLM evaluation.
Concordia AI 安远AI (Brian Tse, CEO)
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Concordia AI: Beijing and Singapore AI safety organisation publishing State of AI Safety in China reports.
Connor Leahy (@NPCollapse)
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The Compendium, co-authored by Connor Leahy: explanation of AI extinction risks and proposed responses.
@hillbig (Daisuke Okanohara 岡野原大輔)
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X account of Daisuke Okanohara, Preferred Networks co-founder: Japanese summaries of AI papers.
IST-DASLab GitHub organization
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IST Austria DAS Lab GitHub organisation (Dan Alistarh): code for GPTQ, SparseGPT, Marlin and AQLM quantization.
Daniel Bourke (@mrdbourke)
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Daniel Bourke's Learn PyTorch for Deep Learning: free hands-on online book and course.
Daniel Han (@danielhanchen)
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Unsloth site, co-founded by Daniel Han: open-source tools for fast fine-tuning and running models locally.
Daniel Kokotajlo (@DKokotajlo)
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AI 2027: scenario forecast of superhuman AI development by Daniel Kokotajlo and co-authors.
Data Hackers
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Data Hackers site: a large Brazilian data science and AI community with a Slack group and podcast.
Data Science by ODS.ai
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Data Science by ODS.ai: Telegram channel of the Open Data Science community, posting ML papers and news.
Data Secrets
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Data Secrets Telegram channel: Russian-language digest of machine learning news.
David Bau (@davidbau)
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National Deep Inference Fabric (NDIF), led by David Bau: NSF infrastructure and nnsight for interpretability on large models.
Dax Raad (@thdxr)
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OpenCode: open-source terminal AI coding agent, from Dax Raad and team.
Daya Guo (DeepSeek)
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DeepSeek-R1 paper (2025), led by Daya Guo, on incentivising reasoning in LLMs with reinforcement learning.
Dean W. Ball (@deanwball)
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Dean W. Ball's Hyperdimensional newsletter on emerging technology and AI governance.
Deep Learning Indaba 2026
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Deep Learning Indaba 2026 site, the annual African machine-learning gathering held in Lagos.
Denis Sexy IT (@denissexy)
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Denis Sexy IT Telegram channel by Denis Shiryaev: Russian-language personal blog on technology and AI.
Doug O'Laughlin (@fabknowledge)
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Doug O'Laughlin's Fabricated Knowledge newsletter on semiconductors and AI hardware economics.
Drew Breunig (@dbreunig)
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Drew Breunig's blog on AI, data and culture, including posts on how long contexts fail.
Dwarkesh Patel (@dwarkesh_sp)
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Dwarkesh Podcast: long-form interviews with AI researchers, founders and thinkers.
Dylan Patel (@dylan522p)
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Dylan Patel's SemiAnalysis newsletter on semiconductors, AI infrastructure and compute economics.
Ed Zitron (@edzitron)
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Ed Zitron's Where's Your Ed At: long-form critiques of AI business models and capital spending.