Chinese AI company Deepseek has unveiled a new training method, Manifold-Constrained Hyper-Connections (mHC), which will make it possible to train large language models more efficiently and at lower ...

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

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 ...

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 ...

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 ...

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

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.

Lin Tian receives funding from the Advanced Strategic Capabilities Accelerator (ASCA) and the Defence Innovation Network. Marian-Andrei Rizoiu receives funding from the Advanced Strategic Capabilities ...

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 ...