Running a large language model is expensive, and a surprising amount of that cost comes down to memory, not computation.

If you've been trying to stream BeamNG.drive to TikTok Live with standard OBS settings, you've likely noticed your high-bitrate 1080p streams getting crushed into blocky, unwatchable messes during ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, announces the launch of its latest core technology — the Efficient Deterministic Quantum State ...

In its effort to focus on meeting the memory demands of the AI data center market, Micron late last year announced it was ...

Took 1st place in Track C and Grand Prize among all 20 competing teams with synthetic data generation technology specialized for MoE quantization Built a dataset using an agent based on Nemotron 3 ...

Arista Networks is a leading provider of Ethernet switches, routers, and other networking hardware used in data centers and cloud computing. The company has been dealing with blistering memory prices, ...

Memory prices are falling, and stock prices of memory companies took a hit, following news from Google Research of a breakthrough that will greatly reduce the amount of memory needed for AI processing ...

Forbes contributors publish independent expert analyses and insights. Tim Bajarin covers the tech industry’s impact on PC and CE markets. This voice experience is generated by AI. Learn more. This ...

The big picture: Google has developed three AI compression algorithms – TurboQuant, PolarQuant, and Quantized Johnson-Lindenstrauss – designed to significantly reduce the memory footprint of large ...

The compression algorithm works by shrinking the data stored by large language models, with Google’s research finding that it can reduce memory usage by at least six times “with zero accuracy loss.” ...