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From sequence to structure, in one sentence.⚡ Today’s Agent Spotlight: Boltz-2 Structure Prediction Agent on ASI:One. Built on Massachusetts Institute of Technology (MIT)’s cutting-edge Boltz-2 model and deployed via NVIDIA's API, this agent generates 3D biomolecular structures just from a natural language prompt. Supports proteins, DNA, RNA, ligands, constraints,...

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Learn more about Boltz-2, the new open source AI model from MIT and Recursion capable of predicting protein binding affinity with unprecedented speed, scale and accuracy. ▪️ Boltz-2 is the first model to combine structure and binding affinity prediction, approaching the accuracy of physics-based free energy perturbation (FEP) calculations while being over 1,000 times faster and less computationally expensive. 💥 The model addresses a critical bottleneck in small molecule drug discovery. ▪️ A powerful tool built on novel machine learning: “By predicting both molecular structure and binding affinity simultaneously with unprecedented speed and scale, Boltz-2 gives R&D teams a powerful tool to triage more effectively and focus resources on the most promising compounds,” says Najat Khan, PhD, Chief R&D Officer and Chief Commercial Officer at Recursion. ▪️ The added power of open source: “Because Boltz-2 is open-source, including its training code, scientists can easily adapt it for specific types of molecules, making it even more powerful as a tool to accelerate discovery," says Regina Barzilay, PhD, MIT School of Engineering Distinguished Professor for AI and Health, AI faculty lead at MIT Jameel Clinic for AI & Health and MIT CSAIL principal investigator. 👉 Learn more, read the preprint, and access Boltz-2 here: 📅 Join us for live presentations, demos and discussions: 📎 MIT Presentation (Cambridge) – Monday, June 9. 📎 NVIDIA #GTC25 (Paris) – Wednesday, June 11. 📎 Molecular Machine Learning Conference - MoML (Montreal) – Tuesday, June 17.

Recursion

15,593 Aufrufe • vor 1 Jahr