Eric Nguyen
@exnx
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PhD in BioEngineering & AI @stanford @HazyResearch @StanfordAILab
Stanford, CA
Joined April 2009
Evo has been published in @Science! A true privilege to work with such an amazing team! So many exciting new experimental results in this emerging field of Generative Genomics, including AI generated and *validated* CRISPR-Cas systems and transposons
A new Science study presents “Evo”—a machine learning model capable of decoding and designing DNA, RNA, and protein sequences, from molecular to genome scale, with unparalleled accuracy. Evo’s ability to predict, generate, and engineer entire genomic sequences could change the way synthetic biology is done. Learn more in this week's issue:
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that's fast! ⚡️
We got early access to some of the very first Nvidia B200’s. We share initial benchmark results and wrote the fastest (public) attention kernel with 925+ BF16 TFLOPs: Since the PTX instruction set released yesterday, @aaryan04 and I have been hard at work at @HazyResearch learning the new instructions and putting them to the silicon.
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Meta chain of thought 😍 Awesome work by @ZiyuX and team!
We have a new position paper on "inference time compute" and what we have been working on in the last few months! We present some theory on why it is necessary, how does it work, why we need it and what does it mean for "super" intelligence.
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RT @w4nderlus7: Today, I’m excited to unveil a project that’s incredibly close to my heart. As a lifelong gamer, I’ve always dreamed of pus…
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Way to go @aditimerch ! What a first phd project!
Excited to have the first project of my PhD out!!! By leveraging Evo's ability to learn relationships across genes (i.e., "know a gene by the company it keeps"), we show that we can engineer highly divergent proteins with retained functionality. 🧵1/3
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Prompt engineered Evo! It's wild to see Evo used to mine *real* biological machinery beyond what's found in nature, and *validated* in the wet lab Incredible work led by @aditimerch, @samuelhking & @BrianHie . I think they're on to something
In new work led by @aditimerch with @samuelhking, we prompt engineer Evo to perform function-guided protein design with high experimental success rates, including designs that go beyond natural sequences. We also release SynGenome, the first AI-generated genomics database. 🧵 1/N
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RT @KhaledSaab11: Our approach to evaluating health AI models continues to evolve! (Phase 1) Medical Benchmarks ➡️ (Phase 2) Patient Actor…
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Love these guys’ work
Phil (@phil_fradkin) and I will be presenting Orthrus ( as a spotlight poster at the Workshop on AI for New Drug Modalities at #NeurIPS2024! Our poster will be up starting 11:40AM in West Meeting Room 109, 110. Excited to be sharing some new results!
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RT @MichaelWornow: Excited to present 🍞 WONDERBREAD at #NeurIPS 2024, a paper on the workflow understanding capabilities of multimodal mode…
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RT @simran_s_arora: I'll be at NeurIPS this week, tues-sat: - Wed 11 am: fast verifiable training of llms with 140x plus lower memory footp…
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RT @ai_with_brains: Today, we report advances in automated neural network architecture design and customization that we have been working o…
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RT @MichaelPoli6: We tackle the complex problem of architecture design for a world where AI is deployed everywhere. How do we balance trade…
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Avanika is amazing!!! She's co-founding a company for enterprise AI agents!
So excited to be launching @rox__ai with the incredible @IshanMkh, Diogo Ribeiro and @shriram_s. The Rox Agent Swarm is the first enterprise ready fleet of AI agents, designed to supercharge the world’s best sellers. Get your Agent Swarm now —> Rox is built for the best, with the best, and by the best (s/o @derhacobian, @amolsingh01, Damon Lin)!!!
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that's pretty cool!
🧬What are protein language models (PLMs) actually learning about biology? Our paper introduces InterPLM - a framework that reveals interpretable features in PLMs using sparse autoencoders, giving us a window into how these models represent protein structure and function. 🧵(1/9)
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Chris always has interesting perspective on new research directions, very thoughtful piece looking back on Evo and looking forward in other domains like physics
An Unserious Person’s Take on Axiomatic Knowledge in the Era of Foundation Models. This post explains why we started the work that led to Evo (HyenaDNA), recently on the cover of Science–thanks to a host of wonderful collaborators at @arcinstitute . It has some odd musing about foundation models and science... and what I got and continue to get wrong about foundation models, @StanfordCRFM. H/t @mzhangio for the memes. If you suffer to the end, this not very funny joke will make more sense... maybe. It's long.
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