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The recording of our seminar on Boltz-1 with Michael Bronstein and VantAI is now public on YouTube! youtube.com/watch?v=mN5pXx…

As lung cancer rates rise in nonsmokers, a troubling trend for the #1 deadliest cancer, we hope more hospitals will adopt tools like Sybil, an AI model built by #JClinic & Mass General Brigham researchers that predicts lung cancer risk up to 6 years in advance. youtu.be/xGSiP8i4VbU

Excited to see our work published in Science Magazine on generating novel disordered proteins with PLMs that selectively localize in biomolecular condensates! An honor to collaborate with Peter G Mikhael Ilan Mitnikov Henry Kilgore Regina Barzilay Richard Young science.org/doi/10.1126/sc…

New paper out! We introduce “LEAPS”, a neural sampling algorithm for discrete distributions via continuous-time Markov chains (“discrete diffusion”). We introduce a novel importance sampling scheme and novel symmetries built into neural networks. arxiv.org/pdf/2502.10843 (1/4)

🤯Mind-blowing keynote by Regina Barzilay on the application of AI in cancer research! 🤖The future is here. Massachusetts Institute of Technology (MIT) MIT Jameel Clinic for AI & Health #MarkSymposium #AIinMedicine

Thrilled to release Boltz-1x! The physical quality of poses was a recurring piece of feedback we received. With Boltz-1x, we use inference-time steering to remove clashes, respect chirality and other physical properties. A few other goodies too. Work led by the amazing Noah Getz

Excited to unveil Boltz-2, our new model capable not only of predicting structures but also binding affinities! Boltz-2 is the first AI model to approach the performance of FEP simulations while being more than 1000x faster! All open-sourced under MIT license! A thread… 🤗🚀

Boltz-1 was always a stepping stone. It’s great to finally share what we’ve been up to since. Boltz-2 puts binding affinity prediction to work—so we can run virtual screens without breaking a sweat. A few other goodies too, go check it out!

A remarkable turnout! Thank you to the 400+ attendees who came to listen to the first-ever Boltz-2 presentation in-person and for asking great questions! We look forward to seeing how Boltz-2 will empower future research in biomolecular structure prediction! 🔥

Did you know the NVIDIA #cuEquivariance library can now accelerate Triangle Attention and Triangle Multiplication operations? Say goodbye to AI model bottlenecks — get up to 2x speedups in training and inference to build and train bigger models. We’re excited that the next-gen

Tenstorrent cares about Boltz as well!

📢 Call for proposals: Boltz small-molecule design collaboration! 🧬 Can we help design your ideal molecule? Can you help us improve our open-source models? Please reach out or share with scientists you know! More details below! It has been great to see the level of excitement