If you've spent any time running local LLMs, you've probably hit the same wall I have. You find the perfect model quantized to 4-bits, just small enough to fit in your GPU's context window. You then ...

For years, the PC industry has been stuck in a rut. Consumers stretched upgrade cycles from three years to five or more, ...

Lightbits Labs Ltd. today is introducing a new architecture aimed at addressing one of the most stubborn bottlenecks in large-scale artificial intelligence inference: the growing mismatch between the ...

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 ...

Training AI demands raw GPU compute. Inference demands something else entirely: memory. The GPUs powering today's models carry limited high-bandwidth memory (HBM) before external memory is ...

Nvidia CEO Jensen Huang recently declared that artificial intelligence (AI) is in its third wave, moving from perception and generation to reasoning. With the rise of agentic AI, now powered by ...

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.

A new attack, dubbed GPUBreach, can induce Rowhammer bit-flips on GPU GDDR6 memories to escalate privileges and lead to a full system compromise. GPUBreach was developed by a team of researchers at ...

Nvidia researchers have introduced a new technique that dramatically reduces how much memory large language models need to track conversation history — by as much as 20x — without modifying the model ...

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

Kioxia GP Series SSD provides GPUs with faster memory access beyond HBM limits Storage Class Memory bridges the performance gap between DRAM and conventional NAND flash storage XL-FLASH prioritizes ...