Tudor Achim
@tachim
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Super excited about all the possible applications for these new protein diffusion generative models from
@namrata_anand2
! The contrast between diffusion for 3D structures vs images is fascinating. Great to see this progress on the structural side.
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👋 We started Harmonic less than a year ago to build Mathematical Superintelligence (MSI). Here is what we’ve done so far. 1/
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Excited to see
@namrata_anand2
work on generative AI models for protein design featured in the New York Times. Lots more to come from her new company, Diffuse Bio!
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Our first result is Aristotle, a language model which advances the state of the art on MiniF2F, the standard dataset of formal mathematics problems statements. We are using Lean 4 for formal verification. 2/
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Super proud of the team!
We are excited to share three major updates today on our path to mathematical superintelligence 🦾
1. A new state-of-the-art of 90% on the MiniF2F benchmark. This beats our previously announced 83% from under a month ago.
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If you’re interested in helping us accelerate the advent of Mathematical Superintelligence, check out our open roles at 6/
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Aristotle currently achieves an 83% success rate with computer algebra assistance, and a 63% proof rate at producing full Lean proofs. For more detail, please see 3/
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We were able to achieve this state of the art performance predominantly with synthetic data, which gives us confidence that this approach can scale to true superintelligence. 4/
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Following up on our diffusion generative models for proteins earlier this year: now we show their effectiveness for fitting density maps. So psyched about how fast this area is developing!
Excited to share results on fitting protein structures to density maps with diffusion models! Our setup uses priors from language models and simultaneously predicts the structure and fits the atomic model to densities, with zero pre- or post-processing. (1/3)
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We are rapidly scaling all aspects of our training and inference, and we’re hiring AI researchers, distributed systems experts, and mathematicians. 5/
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Pretty incredible results from
@diffuse_bio
on designing nanobodies for target proteins. They’re hiring!
I’m excited to share some of our progress at
@Diffuse_Bio
today, about a year and a half into our journey! 1/
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My answer to What are the best companies to work for as a machine learning engineer?
http://t.co/Km9mb3jBfl
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Super excited about all the possible applications for these new protein diffusion generative models from
@namrata_anand2
! The contrast between diffusion for 3D structures vs images is fascinating. Great to see this progress on the structural side.
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Another great answer from fmr WH aide
@MattMcDonaldHPS
: What does it feel like to work directly for the President?
http://qr.ae/03ZU
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Just released: open source package for fully AI-based sequence design and rotamer packing for arbitrary protein backbones, from
@namrata_anand2
. Potential use in designing Sars-CoV2 RBD binders etc. Check it out!
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