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

Large language models already read, write, and answer questions with striking skill. They do this by training on vast libraries of text. Once that training ends, though, the model’s knowledge largely ...

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

Instead of a single, massive LLM, Nvidia's new 'orchestration' paradigm uses a small model to intelligently delegate tasks to a team of tools and specialized models.

In 2025, large language models moved beyond benchmarks to efficiency, reliability, and integration, reshaping how AI is ...

What the firm found challenges some basic assumptions about how this technology really works. The AI firm Anthropic has developed a way to peer inside a large language model and watch what it does as ...

The proliferation of edge AI will require fundamental changes in language models and chip architectures to make inferencing and learning outside of AI data centers a viable option. The initial goal ...

Small Language Models (SLM) are trained on focused datasets, making them very efficient at tasks like analyzing customer feedback, generating product descriptions, or handling specialized industry ...

AI companies could have the legal right to train their large language models on copyrighted works — as long as they obtain copies of those works legally. That’s the upshot of a first-of-its-kind ...