The AI research community continues to find new ways to improve large language models (LLMs), the latest being a new architecture introduced by scientists at Meta and the University of Washington.

Researchers at the Tokyo-based startup Sakana AI have developed a new technique that enables language models to use memory more efficiently, helping enterprises cut the costs of building applications ...

The development of large language models (LLMs) is entering a pivotal phase with the emergence of diffusion-based architectures. These models, spearheaded by Inception Labs through its new Mercury ...

Large language models represent text using tokens, each of which is a few characters. Short words are represented by a single token (like “the” or “it”), whereas larger words may be represented by ...

Transformer-based large language models (LLMs) have considerably advanced our understanding of how meaning is represented in the human brain; however, the validity of increasingly large LLMs is being ...

As vision-centric large language models move on-device, performance measured in raw TOPS is no longer enough. Architectures need to be built around real workloads, memory behavior, and sustained ...