Unlike conventional AI training, which depends on enormous quantities of existing information, the new approach allows models to build predictive capabilities before encountering real-world material.

Researchers explore AI's role in scientific modeling, from historical breakthroughs to modern Bayesian frameworks like ModelSMC.

Anthropic published a guest research essay on November 6, 2026, in which AI for Science grantees Jakob Macke, Daniel Gedon ...

This week, Chromatography Online’s coverage spanned lipidomics-based early cancer detection, career paths in separation ...

Researchers at Tel Aviv University (TAU) and Stanford University have developed a new artificial intelligence training method ...

Event includes announcement of major grant from Schmidt Sciences to boost capacity for AI and computational science ...

Tencent's Hunyuan Research Agent version 2.0 made its debut Monday, claiming to have crossed a threshold that has defined the ambition of AI-for-science research for a decade: instead of solving ...

Scientists spend their careers trying to understand how the world works. Yet even in their own specialties, complete ...

CAS announced its CAS Copilot integration on October 20, bringing curated scientific information into Microsoft’s assistant ...

Through the Young Researchers Institute Fellowship, students are learning how AI can expand access to scientific research, ...

Singapore is expanding the use of artificial intelligence in scientific research and industrial development through a new ...

BEIJING, Oct. 29, 2026 /PRNewswire/ -- Apex Intelligence has released Apex-35B-V1.0, its first model. Built on ...