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 ...
VentureBeat

Breaking through AI’s memory wall with token warehousing

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 ...
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 ...
VentureBeat

DeepSeek’s conditional memory fixes silent LLM waste: GPU cycles lost to static lookups

When an enterprise LLM retrieves a product name, technical specification, or standard contract clause, it's using expensive GPU computation designed for complex reasoning — just to access static ...