Alex Rives ✓
@alexrives · Brooklyn, NY · joined 07 Apr 2009
AI for scientific discovery. Head of Science, Biohub. Founder and scientific director of the ESM project.
14 764Followers
898Following
397Posts total
1.6MViews on collected posts
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@alexrives This is awesome. Seeing the molecular machinery may open up entirely new frontiers to understand aging.
4.6K views · 119 likes
· 0 reposts · 2 replies
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Together with UC Berkeley we are announcing the laser phase plate - a breakthrough in atomic resolution imaging. This is the brightest continuous wave laser in the world, 100 million times the intensity of the surface of the sun.
Phase contrast plays an important role in https:/
661K views · 4K likes
· 567 reposts · 92 replies
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Great talking with RJ and Brandon on the Latent Space AI for Science podcast, about protein language models, scaling in biology, and the new ESMFold2.
10.5K views · 52 likes
· 9 reposts · 5 replies
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🆕Biohub’s Protein World Model: ESMC-6B, ESMFold2, 6.8B proteins, 1.1B structures, antibody design, SAEs, & the bitter lesson for biology https://t.co/2PGoHjttCS
@biohub Head of Science @alexrives explains why biology may scale like language modeling, how metagenomics unlocked
24.2K views · 39 likes
· 12 reposts · 7 replies
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@alexrives Amazing 👏
Congrats to you and the ESM team.
7.6K views · 71 likes
· 2 reposts · 6 replies
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At @Biohub, our goal is to build models that accelerate scientific discovery and progress toward the cure to disease. We’re releasing all of this under MIT license allowing commercial and non-commercial use.
Read more here: https://t.co/Rt0Vo4QnSA
30.9K views · 176 likes
· 33 reposts · 3 replies
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We’re also releasing the largest atlas of protein structure and function. With 6.8 billion proteins, and 1.1 billion predicted structures, it enables analysis and protein discovery at the scale of life. https://t.co/trvtAODPP9
16.6K views · 133 likes
· 21 reposts · 3 replies
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We designed miniproteins and antibodies for five targets that are important in cancer and immunology. We found binders with nanomolar affinities for all, and sometimes picomolar affinities, testing just 84 designs per target and modality.
Scaling compute at inference time https:
9.5K views · 62 likes
· 7 reposts · 3 replies
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ESMFold2 is blazing fast and has state of the art accuracy across benchmarks for structure prediction, especially for the challenging problem of predicting protein interactions, including the interaction of antibodies with their targets. https://t.co/BNUAux6uC5
14.1K views · 81 likes
· 7 reposts · 2 replies
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Today we're announcing ESMFold2, an open scientific engine to power prediction, design, and discovery across protein biology.
The new model delivers state of the art performance on protein interactions, especially antibodies, a critical modality for therapeutics.
We have https:
625.5K views · 1.6K likes
· 447 reposts · 76 replies
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GIF
Scaling laws are powering AI. It’s time to scale biology.
Today we’re launching the Virtual Biology Initiative to generate the data to unlock scaling laws in biology and build accurate predictive models of the cell.
Digital representations of proteins are already expanding our
133.3K views · 748 likes
· 137 reposts · 38 replies
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Sequence is all you need. Protein language models set a new state of the art for predicting the clinical effect of genetic variations.
https://t.co/RxNRgZrNgL
19.3K views · 117 likes
· 10 reposts · 3 replies
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To me, this is a very satisfying result from a theoretical perspective, demonstrating in a sense that "sequence is all you need" for variant effect prediction. The model we introduce, #VESM (Variant-effect ESM), is entirely derived from within the ESM family without using any htt
20.1K views · 38 likes
· 3 reposts · 3 replies
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Growth & engagement
How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.
Views per post
20.1K31 Mar
19.3K1 Apr
133.3K29 Apr
625.5K27 May
14.1K
9.5K
16.6K
30.9K
7.6K
24.2K
10.5K28 May
661K11 Jun
20.5K
4.6K13 Jun
Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
0.22%31 Mar
0.68%1 Apr
0.72%29 Apr
0.36%27 May
0.65%
0.77%
0.97%
0.71%
1.03%
0.25%
0.63%28 May
0.71%11 Jun
1.29%
2.60%13 Jun
Reactions — likes, reposts, replies and quotes — divided by views.
What the audience does
Likes60.8%7 459 in total
Reposts10.4%1 278 in total
Replies2.0%248 in total
Quotes2.1%263 in total
Bookmarks24.6%3 017 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.
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Frequently asked questions about @alexrives
How many followers does @alexrives have?
14 764 followers.
How many posts has @alexrives published?
397 posts.
How do posts by @alexrives perform?
Collected posts: 14. Views: 1 597 837. Likes: 7 459.