Running a large language model is expensive, and a surprising amount of that cost comes down to memory, not computation.

Reducing the precision of model weights can make deep neural networks run faster in less GPU memory, while preserving model accuracy. If ever there were a salient example of a counter-intuitive ...

The reason why large language models are called ‘large’ is not because of how smart they are, but as a factor of their sheer size in bytes. At billions of parameters at four bytes each, they pose a ...

Within 24 hours of the release, community members began porting the algorithm to popular local AI libraries like MLX for Apple Silicon and llama.cpp.

Fine-tuning large language models (LLMs) might sound like a task reserved for tech wizards with endless resources, but the reality is far more approachable—and surprisingly exciting. If you’ve ever ...

ChatRTX is a demo app that lets you personalize a GPT large language model (LLM) connected to your own content—docs, notes, images, or other data. Leveraging retrieval-augmented generation (RAG), ...

Meta Platforms Inc. is striving to make its popular open-source large language models more accessible with the release of “quantized” versions of the Llama 3.2 1B and Llama 3B models, designed to run ...

Opportunities for agentic AI. AI agents go beyond basic in-context learning by enabling LLMs to iteratively plan, reason, and ...

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 ...