As enterprise AI becomes more complex, AI architectures can no longer treat context as temporary.
As inference workloads evolve from discrete question-and-answer exchanges into persistent, multi-step agentic systems, GPU ...
Apple's rumored M5 Ultra and M7 Ultra chips could dramatically expand the Mac Studio's unified memory. Here's why that's ...
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 ...
IEEE Spectrum on MSN
Stacking chips sideways gives AI more memory
Solving a tricky 3D integration problem could boost bandwidth and keep chips cooler ...
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 ...
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 ...
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 ...
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 ...
Earlier this year, SDxCentral explored the market push behind AI inference – the process where a trained machine learning ...
For decades, Micron Technology made one of computing’s less glamorous essentials: memory chips. Then the artificial intelligence boom made that hardware one of the industry’s most sought-after ...
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