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Eugene Yan
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recsys-nlp-graph — 🛒 Simple recommender with matrix factorization, graph, and NLP. Beating the regular collaborative filtering baseline.
recsys matrix recommender
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11 September
Computer science professor who works on fast data processing; co-author of the simdjson parser and a weekly blogger about software performance since 2004.
What should be obvious is that inference, running a large language model, is the part that has to be cheap. Most of our hardware was not designed for that. LLM inference is limited by bandwidth. You do a great many matrix-vector multiplications against a huge weight matrix, and you barely reuse those weights. It is closer to streaming a video than to running a simulation or drawing a scene in a game. Graphics processors from Nvidia and others were built for something else. They pileed compute first, then bolted on high-bandwidth memory. It is expensive. An obvious answer is to invert the desi… LLMs Related
20 August
Co-founded Neuralink and founded Science Corp, which is building a retinal implant; writes about neural interfaces and biology.
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because if you can if you get vision, hearing, balance, and a kilobit per second of motor control, you're halfway to the Matrix.
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2 June
Software developer and entrepreneur; co-founder of Heroku, author of The Twelve-Factor App, and a researcher at Ink & Switch.
15 September 2025
Member of technical staff at Anthropic. He has led ML/AI teams at Amazon, Alibaba and Lazada, and writes about LLMs, recommender systems and engineering at eugeneyan.com.
14 September 2025
Member of technical staff at Anthropic. He has led ML/AI teams at Amazon, Alibaba and Lazada, and writes about LLMs, recommender systems and engineering at eugeneyan.com.
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They excel at predicting what a user will click or buy next, but can't be steered via natural language or reason on their choices.
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eugeneyan.com
Member of technical staff at Anthropic. He has led ML/AI teams at Amazon, Alibaba and Lazada, and writes about LLMs, recommender systems and engineering at eugeneyan.com.
10 July 2025
Cyborg anthropologist and UX designer; author of Calm Technology and co-founder of the geolocation startup Geoloqi.
4 June 2025
Member of technical staff at Anthropic. He has led ML/AI teams at Amazon, Alibaba and Lazada, and writes about LLMs, recommender systems and engineering at eugeneyan.com.
8 April 2025
Member of technical staff at Anthropic. He has led ML/AI teams at Amazon, Alibaba and Lazada, and writes about LLMs, recommender systems and engineering at eugeneyan.com.
Can't wait for when I can vibe code a production recommender system. Until then, here's some system designs: • Retrieval vs. Ranking: eugeneyan.com/writing/syst... • Real-time retrieval: eugeneyan.com/writing/real... • Personalization: eugeneyan.com
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25 September 2023
Mathematical biologist; Senior Lecturer in the Department of Mathematical Sciences at the University of Bath and author of The Maths of Life and Death and How to Expect the Unexpected.
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A korrent is a belief a person has stated in their own words: one
sentence stating the claim, backed by a quote and a source, kept at
korrents.com .
Under a name here, the quoted block is what they actually said.
The korrent beneath it is the claim those words support, in
korrents' wording — tap it to see the record, its source, and who
else holds it.
Nobody here wrote their own korrents. They are compiled from public
statements, and a person can change their mind, which is recorded too.
Got it
About the English under a post
Some people here publish in a language other than English. Where they
do, this site shows a machine translation beneath the post, in
this typeface — the site's own, not theirs.
The post itself is never changed, moved or hidden: what is set in the
serif above is exactly what the person published, and it is what to
quote them on. A translation can be wrong in ways that matter,
especially about tone.
Only the post's own words are translated. A quoted post, a linked
article and a belief on korrents.com
are left in their original language.
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