🔥The 9th Round of Easy Loan, Earn $40 Reward is in progress❗️ ⏰ Promotion Period: January 15th - Feburary 15th, 2025 👉 Register now and check more details at gate.io/campaigns/358

Thrilled to announce Boltz-1, the first open-source and commercially available model to achieve AlphaFold3-level accuracy on biomolecular structure prediction! An exciting collaboration with Jeremy Wohlwend, Saro and an amazing team at MIT and Genesis Therapeutics. A thread!

OMG is this a complete AF3-like model that's actually open, not weird pretend open like most of the others?? (I believe Ligo is open but no model weights yet?) "training and inference code, model weights, and datasets" are MIT licensed

Excited to announce Boltz-1: the first fully open-source AlphaFold3-level model!

Give this some love - open-source biology AI needs more recognition! huggingface.co/boltz-communit… by Gabriele Corso and team

MIT and Genesis Therapeutics released Boltz-1, an open-source model matching AlphaFold3's accuracy in predicting biological structures Available for researchers worldwide under MIT license x.com/gabricorso/sta…

We’re excited to release another update to the Boltz repo: v0.3.0. This release includes several important features, including our confidence model and low memory mode. Give it a try! github.com/jwohlwend/boltz

New major update to Boltz-1 integrating the confidence model and memory-efficient inference! Happy Thanksgiving! 🤗🦃 github.com/jwohlwend/boltz

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… 🤗🚀

Scalable computational binding affinity prediction is a crucial and long-standing scientific challenge. Physics-based methods like FEP are accurate but slow and expensive. Docking is fast but noisy. Deep learning models haven’t matched the reliability of FEP—until now.

Beautiful work! Weights on HF here: huggingface.co/boltz-community

Hailing from quantum chemistry and physics-based modeling, this feels like a seminal moment. And one that I would not have predicted 10 years ago. Kudos! and Kudos for being on the side of openness.

A team led by Regina Barzilay, a computer science professor at Massachusetts Institute of Technology (MIT), has launched Boltz-2, an algorithm that unites protein folding and prediction of small-molecule binding affinity in one package. cen.acs.org/pharmaceutical…

For those already using Boltz-2 affinity prediction, we realized that there was a bit of confusion around the different outputs from the models and in what contexts each should be used. We've added more details in the docs. A summary below.

Absolutely thrilled to announce the availability of cuEquivariance v0.5 and our contributions to Boltz-2! cuEquivariance v0.5 is a huge release -- now including accelerated triangle attention and multiplication kernels, fundamental to performance of next-gen geometry-aware NNs.

The team at @NVIDIA has done such amazing work accelerating Boltz-2 through novel CUDA kernels and deploying Boltz-2 as NVIDIA’s NIM! The kernels are live on the Boltz repo, and you can run the model with 2x training & inference speedup and large memory savings!🧵#cuEquivariance

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 5x speedups in training and inference to build and train bigger models. We’re excited that the next-gen

Open science, activated. Since the release of Boltz-2 last Friday – the new open-source protein structure and protein binding affinity model from Massachusetts Institute of Technology (MIT) and Recursion – we’ve been introducing the model to the broader community and the reception has been terrific. 🔹At #GTCParis

Wow apparently Boltz-2 was used as example by no other than John Jumper ☺️🤗