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st8ic t1_ja60y60 wrote

ah yes, salesforce.com, the premier synthetic biology company

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Measurex2 t1_ja6ca1j wrote

They've been going after the Healthcare vertical heavily for the last decade, and Benioff has donated like half a billion to hospitals and research from his own wallet.

https://www.salesforce.com/solutions/industries/healthcare/pharma/health-care-innovation/

I buy every dip in Salesforce because they keep delivering in some many interesting ways. The news of the co-CEO and all their product and department leads leaving dropped their stock in Q4. It's up 25% since then.

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Franc000 t1_ja894hj wrote

Who cares if the research is actually good?

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walk-the-rock t1_ja6sp5s wrote

Richard Socher (chief scientist at salesforce) is one of the world leaders in natural language processing within ML/AI

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MysteryInc152 OP t1_ja3hozj wrote

>Deep-learning language models have shown promise in various biotechnological applications, including protein design and engineering. Here we describe ProGen, a language model that can generate protein sequences with a predictable function across large protein families, akin to generating grammatically and semantically correct natural language sentences on diverse topics. The model was trained on 280 million protein sequences from >19,000 families and is augmented with control tags specifying protein properties. ProGen can be further fine-tuned to curated sequences and tags to improve controllable generation performance of proteins from families with sufficient homologous samples. Artificial proteins fine-tuned to five distinct lysozyme families showed similar catalytic efficiencies as natural lysozymes, with sequence identity to natural proteins as low as 31.4%. ProGen is readily adapted to diverse protein families, as we demonstrate with chorismate mutase and malate dehydrogenase.

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hackinthebochs t1_ja6tpln wrote

At what point do we stop calling it a language model?

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uhules t1_jadfp2z wrote

At the point where it stops being a P(w|h) estimator.

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