Microsoft's Phi-4-reasoning-vision-15B uses careful data curation and selective reasoning to compete with models trained on ...

As large language models (LLMs) gain momentum worldwide, there’s a growing need for reliable ways to measure their performance. Benchmarks that evaluate LLM outputs allow developers to track ...

Forbes contributors publish independent expert analyses and insights. Chief Analyst & CEO, NAND Research. Mistral AI and NVIDIA launched Mistral NeMo 12B, a state-of-the-art language model for ...

These new models are specially trained to recognize when an LLM is potentially going off the rails. If they don’t like how an interaction is going, they have the power to stop it. Of course, every ...

A meta-analysis suggests that large language model-simplified radiology reports improve patient understanding and readability ...

While Large Language Models (LLMs) like GPT-3 and GPT-4 have quickly become synonymous with AI, LLM mass deployments in both training and inference applications have, to date, been predominately cloud ...

Explore how vision-language-action models like Helix, GR00T N1, and RT-1 are enabling robots to understand instructions and act autonomously.

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 original version of this story appeared in Quanta Magazine. Large language models work well because they’re so large. The latest models from OpenAI, Meta, and DeepSeek use hundreds of billions of ...

If you are a tech fanatic, you may have heard of the Mu Language Model from Microsoft. It is an SLM, or a Small Language Model, that runs on your device locally. Unlike cloud-dependent AIs, MU ...