With reported 3x speed gains and limited degradation in output quality, the method targets one of the biggest pain points in production AI systems: latency at scale.

Meta Platforms Inc. has open-sourced four language models that implement an emerging machine learning approach known as multi-token prediction. VentureBeat reported the release of the models today.

Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...

In a recent study, researchers at Meta, Ecole des Ponts ParisTech and Université Paris-Saclay suggest improving the accuracy and speed of AI large language models (LLMs) by making them predict ...

A new research paper from Apple details a technique that speeds up large language model responses, while preserving output quality. Here are the details. Traditionally, LLMs generate text one token at ...

There are numerous ways to run large language models such as DeepSeek, Claude or Meta's Llama locally on your laptop, including Ollama and Modular's Max platform. But if you want to fully control the ...