MIT researchers have built an AI language model that learns the internal coding patterns of a yeast species widely used to manufacture protein-based drugs, then rewrites gene sequences to push protein ...

A research team at the University of Würzburg has deciphered another aspect of poxviral gene activation. They have revealed a unique viral mechanism: A molecular ring anchors the viral copying machine ...

How does our DNA store the massive amount of information needed to build a human being? And what happens when it's stored incorrectly? Jesse Dixon, MD, Ph.D., has spent years studying the way this ...

From Austria’s hydropower tradition to African grid-scale platforms, enso’s “system orchestrator” model fuses technology, finance and governance into investment-ready energy ecosystems that deliver ...

This project evaluates how well Mesa currently supports building agent models based on established behavioral theories. The suggested approach is hands-on: implement example models, document what ...

Project Genie allows people outside of Google to try the company's Genie 3 world model. (Google) This past summer, Google DeepMind debuted Genie 3. It’s what’s known as a world world, an AI system ...

Add Yahoo as a preferred source to see more of our stories on Google. [Getty Images] An AI model developed by Google's DeepMind could transform our understanding of DNA - the complete recipe for ...

Artificial intelligence has gotten a bad reputation lately, and often for good reason. But a team of scientists at Google’s DeepMind now claims to have found a revolutionary use case for AI: helping ...

An AI model developed by Google's DeepMind could transform our understanding of DNA - the complete recipe for building and running the human body - and its impact on disease and medicine discovery, ...

The overhaul of the state of Washington’s financial management system is highlighting the need to have focused priorities and collaboration among state agencies and their private-sector partners.

Abstract: Temporal graph representation learning seeks to capture the intrinsic evolution of nodes in temporal graphs for various applications. While existing models primarily learn node ...