Enterprises locked in GPU capacity during the AI scramble. Now utilization sits at 5% and the bill is due. Here's what the data says about where the market is heading.

Shimon Ben-David, CTO, WEKA and Matt Marshall, Founder & CEO, VentureBeat As agentic AI moves from experiments to real production workloads, a quiet but serious infrastructure problem is coming into ...

The GPUs powering today's models carry limited high-bandwidth memory (HBM) before external memory is required—that's the memory wall, and at inference scale, every model hits it. As the industry ...

Most infrastructure decisions look fine on paper until real AI workloads begin running at scale. Then performance issues ...

The growing imbalance between the amount of data that needs to be processed to train large language models (LLMs) and the inability to move that data back and forth fast enough between memories and ...

Tensormesh Inc. has hit upon a way to make artificial intelligence inference more efficient by eliminating the need for ...

But there’s one spec that has caused some concern among Ars staffers and others with their eyes on the Steam Machine: The GPU comes with just 8GB of dedicated graphics RAM, an amount that is steadily ...

Korean chip startup XCENA raised $135M at a $570M valuation to solve the AI memory bottleneck. Learn how their CXL-based MX1 ...

If you've ever watched your games or rendering processes struggle to run out of nowhere, despite Task Manager telling you your GPU is well below max capacity, you've been lied to. Windows Task Manager ...

Whether you’re a gamer trying to play recent AAA titles at high resolutions and maxed-out settings or an AI enthusiast trying to run models locally, we’ve reached the point where a GPU with 8GB of ...

Nvidia and Microsoft are attempting to create the first compelling PC upgrade cycle in years by moving AI agents from cloud servers to local devices, reducing latency and costs while challenging Apple ...