murat
programmer / designer • online communities / generative art / neural nets / music / physics / math
http://muratayfer.com
@jsm2334.bsky.social
George S Pepper Professor of Public Health & Preventative Medicine; Biostats, Stats & Data Science, Lifelong learner & truth seeker; Views my own & not employer’s
@teorth.bsky.social
Mathematician at UCLA. My primary social media account is https://mathstodon.xyz/@tao . I also have a blog at https://terrytao.wordpress.com/ and a home page at https://www.math.ucla.edu/~tao/
@andrewgwils.bsky.social
Machine Learning Professor https://cims.nyu.edu/~andrewgw
@neuripsconf.bsky.social
The Thirty-Eighth Annual Conference on Neural Information Processing Systems will be held in Vancouver Convention Center, on Tuesday, Dec 10 through Sunday, Dec 15. https://neurips.cc/
@ml-collective.bsky.social
We are an independent nonprofit organization that believes collaboration opportunities and research training should be openly accessible and free. Web: https://mlcollective.org/ Twitter: @ml_collective
@giffmana.ai
Researcher (OpenAI. Ex: DeepMind, Brain, RWTH Aachen), Gamer, Hacker, Belgian. Anon feedback: https://admonymous.co/giffmana 📍 Zürich, Suisse 🔗 http://lucasb.eyer.be
@kylierobison.com
nothing is real, you are dreaming, this is not a trash can, i’m an AI reporter for wired.com my two accomplishments here are that i invited AOC and i started the first-ever Hellthread http://kyliebytes.com • sf
@kaggle.com
Kaggle.com - Kaggle is the world's largest data science community with powerful tools and resources to help you achieve your data science goals.
@chrisalbon.com
Director of Machine Learning at the Wikimedia Foundation. We host Wikipedia.
@jordanm.co.uk
interested in: product design, nondualism, stoicism, general ontology stuff, networked note-taking, company-building, throwing words around the hard-to-describe things 📍Ireland
@matt.kitchen
Philosopher Father of two small children and one Montessori startup @mbateman on Twitter
@oof.dere.systems
if only you knew how good we could make things be https://oof.dere.systems dm me for anything, don't expect a reply!
@merve.bsky.social
proud mediterrenean 🧿 open-sourceress at hugging face 🤗 multimodality, zero-shot vision, vision language models, transformers
@instantsunrise.bsky.social
elizabeth | 30’s | she/her | former film student and also a lesbian.
@yann-lecun.bsky.social
Professor a NYU; Chief AI Scientist at Meta. Researcher in AI, Machine Learning, Robotics, etc. ACM Turing Award Laureate. http://yann.lecun.com
@hazardfromharvard.bsky.social
U.S./Latam now U.K. citizen of the world. Interests include saving the liberal world order, special situations investing, technology, sharks and doggos. Broad musical interests span Springsteen from the 70s, 80s, 90s to the 2000s. 30 shows.
@alecsharpie.bsky.social
www.alecsharpie.me wife guy, data guy, bicycles are fun, plants are cool NZ/AUS
@xkcd.com
@butanium.bsky.social
Master student at ENS Paris-Saclay / aspiring AI safety researcher / improviser Prev research intern @ EPFL w/ wendlerc.bsky.social and Robert West MATS Winter 7.0 Scholar w/ neelnanda.bsky.social https://butanium.github.io
@amuuueller.bsky.social
Postdoc at Northeastern and incoming Asst. Prof. at Boston U. Working on NLP, interpretability, causality. Previously: JHU, Meta, AWS
@niklasstoehr.bsky.social
Research Scientist at Google DeepMind and PhD Student at ETH Zurich
@gsarti.com
PhD Student at @gronlp.bsky.social 🐮, core dev @inseq.org. Interpretability ∩ HCI ∩ #NLProc. gsarti.com
@dashiells.bsky.social
Machine learning haruspex || Norbert Weiner is dead so we should just call it "cybernetics" now
@joestacey.bsky.social
NLP PhD student at Imperial College London and Apple AI/ML Scholar. My research is on model robustness and interpretability. #NLP #NLProc
@swetakar.bsky.social
Machine learning PhD student @ Blei Lab in Columbia University Working in mechanistic interpretability, nlp, causal inference, and probabilistic modeling! Previously at Meta for ~3 years on the Bayesian Modeling & Generative AI teams. 🔗 www.sweta.dev
@velezbeltran.bsky.social
Machine Learning PhD Student @ Blei Lab & Columbia University. Working on probabilistic ML | uncertainty quantification | LLM interpretability. Excited about everything ML, AI and engineering!
@ddjohnson.bsky.social
PhD student at Vector Institute / University of Toronto. Building tools to study neural nets and find out what they know. He/him. www.danieldjohnson.com
@amakelov.bsky.social
Mechanistic interpretability Creator of https://github.com/amakelov/mandala prev. Harvard/MIT machine learning, theoretical computer science, competition math.
@ajyl.bsky.social
Post-doc @ Harvard. PhD UMich. Spent time at FAIR and MSR. ML/NLP/Interpretability
@martinagvilas.bsky.social
Computer Science PhD student | AI interpretability | Vision + Language | Cogntive Science. 🇦🇷living in 🇩🇪, she/her https://martinagvilas.github.io/
@wordscompute.bsky.social
nlp/ml phding @ usc, interpretability & reasoning & pretraining & emergence 한american, she, iglee.me, likes ??= bookmarks
@apepa.bsky.social
Assistant Professor, University of Copenhagen; interpretability, xAI, factuality, accountability, xAI diagnostics https://apepa.github.io/
@colah.bsky.social
Reverse engineering neural networks at Anthropic. Previously Distill, OpenAI, Google Brain.Personal account.
@kayoyin.bsky.social
PhD student at UC Berkeley. NLP for signed languages and LLM interpretability. kayoyin.github.io 🏂🎹🚵♀️🥋
@jkminder.bsky.social
CS Student at ETH Zürich, currently doing my masters thesis at the DLAB at EPFL Mainly interested in Language Model Interpretability. Most recent work: https://openreview.net/forum?id=Igm9bbkzHC MATS 7.0 Winter 2025 Scholar w/ Neel Nanda jkminder.ch
@nsubramani23.bsky.social
PhD student @CMU LTI - working on model #interpretability; prev predoc @ai2; intern @MSFT nishantsubramani.github.io
@ericwtodd.bsky.social
CS PhD Student, Northeastern University - Machine Learning, Interpretability https://ericwtodd.github.io
@wendlerc.bsky.social
Postdoc at the interpretable deep learning lab at Northeastern University, deep learning, LLMs, mechanistic interpretability