XDA Developers on MSN
TurboQuant tackles the hidden memory problem that's been limiting your local LLMs
A paper from Google could make local LLMs even easier to run.
Morning Overview on MSN
Google says TurboQuant cuts LLM KV-cache memory use 6x, boosts speed
Google researchers have published a new quantization technique called TurboQuant that compresses the key-value (KV) cache in ...
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.” [ ...
The biggest memory burden for LLMs is the key-value cache, which stores conversational context as users interact with AI ...
That much was clear in 2025, when we first saw China's DeepSeek — a slimmer, lighter LLM that required way less data center ...
Tech Xplore on MSN
Holographic storage approach packs more data into the same space by encoding three properties of light
Researchers have developed a holographic data storage approach that stores and retrieves information in three dimensions by ...
Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...
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