Google researchers have revealed that memory and interconnect are the primary bottlenecks for LLM inference, not compute power, as memory bandwidth lags 4.7x behind.

Nvidia’s Rubin platform is not just another chip launch, it is a full-stack bet on how the next decade of artificial intelligence will be powered. By pairing new silicon with a tightly integrated ...

GTC, which began Monday and runs through Thursday, features 900+ sessions. More than 200,000 developers, researchers, and data scientists from 50+ countries have registered for the event. At his GTC ...

TeleChat3 series – China Telecom’s TeleAI released the first large-scale Mixture-of-Experts (MoE) models trained entirely on ...

As enterprises seek alternatives to concentrated GPU markets, demonstrations of production-grade performance with diverse ...

As capable as artificial intelligence (AI) deep learning algorithms have become, the human brain still vastly outperforms silicon-based neural networks when it comes to energy efficiency. In efforts ...

How best to run AI inference models is a current topic of much debate as a wide breadth of systems companies look to add AI to a variety of systems, spurring both hardware innovation and the need to ...

RENO, Nev.--(BUSINESS WIRE)--Positron AI, the premier company for American-made semiconductors and inference hardware, today announced the close of a $51.6 million oversubscribed Series A funding ...

A team of researchers from Drexel University's Electrical and Computer Engineering department has been awarded the Best Paper Award at the 21st ACM International Conference on Computing Frontiers ...

Deep Learning is probably the most popular form of machine learning at this time. Although not every problem boils down to a deep learning model, in domains such as computer vision and natural ...