What could scaling unlock for biology? Introducing ProGen3- our next AI foundation models for protein generation. We develop compute-optimal scaling laws up to 46B parameters on 1.5T tokens with real evidence in the wet lab. +we solve a new set of challenges for drug discovery

Training on more data and increasing the capacity of our language models = better understanding of proteins and ability to generate viable diverse sequences. We are on a clear trajectory.

One of the most important aspects: Alignment of our foundation models to laboratory data improves its utility for functional tasks. Larger models are better at alignment. + easter egg that our large models are good at span generation

This is not purely an academic endeavor. We ultimately evaluate our progress at Profluent based on our ability to create positive value for society. So we tackled two challenges in biology.

1. We took 20 disease targets with approved therapies treating 7M people and yielding $660B in sales. Can we design antibodies that match performance in one shot? Yes + they are materially different across all CDRs and framework regions. We call these OpenAntibodies-- more soon.

2. Gene editors, especially cas9, are quite large, posing practical issues. Could we design ultra-compact cas proteins? Yes, we designed functional proteins that could enable single AAV delivery. Really excited for implications for unaddressable targets and epigenome editing too

☀️The future is bright. We're in the early days of what will sweep biology and design cures to disease. Learn more, license our molecules, or get early access to our API below Fortune:

What happens when you combine every AI? It's time for something better than ChatGPT...

Can we expect an open weights release on the @huggingface hub? Would be hugely impactful.

Congrats! Cool stuff! Will there be a preprint describing OpenAntibodies and the small Cas as well?

Hi Ali, Congrats，will the training dataset be shared？

congrats to the team! looking forward to digging in.