In 2026, here's what you can expect from the AI industry: new architectures, smaller models, world models, reliable agents, ...

Here is the AI research roadmap for 2026: how agents that learn, self-correct, and simulate the real world will redefine ...

These days, large language models can handle increasingly complex tasks, writing complex code and engaging in sophisticated ...

Step aside, LLMs. The next big step for AI is learning, reconstructing and simulating the dynamics of the real world.

Top AI researchers like Fei-Fei Li and Yann LeCun are developing world models, which don't rely solely on language.

anthropomorphism: When humans tend to give nonhuman objects humanlike characteristics. In AI, this can include believing a chatbot is more humanlike and aware than it actually is, like believing it's ...

A biologically grounded computational model built to mimic real neural circuits, not trained on animal data, learned a visual categorization task just as actual lab animals do, matching their accuracy ...

The paper comes at a time when most AI start-ups have been focusing on turning AI capabilities in LLMs into agents and other ...

These aren’t predictions—they’re the first visible signs of a global transformation already underway. AI is no longer ...

AI isn’t neutral in women’s health. It involves learning from visibility gaps shaped by brand safety, search authority, and ...

Army officers interested in transferring will be able to apply through the service’s Voluntary Transfer Incentive Program beginning Jan. 5.

NOAA is using those traditional forecasting models as frameworks for its new AI forecasting systems. The agency has estimated that the AI programs will require between 91% and 99% less computing ...