Deep learning for DFT
In Density Functional Theory, the exchange correlation functional captures the complex relationship between its input—the electron density — and its output: the exchange-correlation energy. The electron density is represented as a large, irregular point cloud,…
DFT for drug and material discovery
Density Functional Theory (DFT) is the workhorse method in chemistry and physics for predicting the formation and properties of molecules and materials. Among many other applications, it plays a crucial role in screening pipelines for…
Breaking bonds, breaking ground: Advancing the accuracy of computational chemistry with deep learning
Microsoft researchers achieved a breakthrough in the accuracy of DFT, a method for predicting the properties of molecules and materials, by using deep learning. This work can lead to better batteries, green fertilizers, precision drug…
What is Density Functional Theory (DFT)?
In this video, Microsoft’s Chris Bishop, Technical Fellow and Director of Microsoft Research AI for Science, explains how Microsoft researchers achieved a breakthrough in the accuracy of density functional theory (DFT) and the challenges they…
Transforming Tumor Boards: AI Agents and the New Era of Personalized Cancer Care
In this fireside chat, Shrey Jain, Product Lead of the Healthcare Agent Orchestrator, joins Eric Horvitz, Chief Scientific Officer at Microsoft, to explore how AI agents are revolutionizing personalized cancer care. They delve into the…
New methods boost reasoning in small and large language models
New techniques are reimagining how LLMs reason. By combining symbolic logic, mathematical rigor, and adaptive planning, these methods enable models to tackle complex, real-world problems across a variety of fields.