Nvidia shrinks LLM memory 20x without changing model weights

Nvidia's KV Cache Transform Coding (KVTC) compresses LLM key-value cache by 20x without model changes, cutting GPU memory costs and time-to-first-token by up to 8x for multi-turn AI applications.

Nvidia BlueField-4 STX adds a context memory layer to storage to close the agentic AI throughput gap

Nvidia's BlueField-4 STX reference architecture inserts a dedicated context memory layer between GPUs and traditional storage, claiming 5x token throughput and 4x energy efficiency for agentic AI ...

New memory architecture targets AI inference bottlenecks

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 ...
Ars Technica

Testing shows why the Steam Machine’s 8GB of graphics RAM could be a problem

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 ...
Semiconductor Engineering

Memory Wall Problem Grows With LLMs

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 ...
TweakTown

Meta's huge 16,384 NVIDIA H100 AI GPU cluster: HBM3 memory crashed half of Llama 3 training

Meta released a new study detailing its Llama 3 405B model training, which took 54 days with the 16,384 NVIDIA H100 AI GPU cluster. During that time, 419 unexpected component failures occurred, with ...
TechSpot

AMD could increase graphics card prices by 10% due to memory shortage crisis

Serving tech enthusiasts for over 25 years. TechSpot means tech analysis and advice you can trust. Ripple effect: It seems fears that the global memory shortage and resulting high prices could impact ...