Decrypt

Google Shrinks AI Memory With No Accuracy Loss—But There's a Catch

The technique reduces the memory required to run large language models as context windows grow, a key constraint on AI ...

IndexCache, a new sparse attention optimizer, delivers 1.82x faster inference on long-context AI models

Researchers at Tsinghua University and Z.ai built IndexCache to eliminate redundant computation in sparse attention models ...
DIGITIMES

In-depth: Google TurboQuant cuts LLM memory 6x, resets AI inference cost curve

Google has introduced TurboQuant, a compression algorithm that reduces large language model (LLM) memory usage by at least 6x ...

Alphabet Just Crashed The Memory Trade: Sandisk Looks Like The Winner (Upgrade)

Sandisk Corp.’s NAND thesis stays strong. Learn why the SNDK stock dip may be headline-driven and why it could retest highs.

Google's new TurboQuant algorithm speeds up AI memory 8x, cutting costs by 50% or more

Within 24 hours of the release, community members began porting the algorithm to popular local AI libraries like MLX for ...
TweakTown

Google's TurboQuant cuts AI working memory by 6x, but it won't fix the global RAM shortage

Google's new TurboQuant algorithm could slash AI working memory by 6x, but don't expect it to fix the broader RAM shortage ...

The Artificial Intelligence (AI) Trade Is Splitting in Two. Here's How to Pick the Right Side in 2026.

Investors should know the difference between AI training and AI inference.
Phys.org

Inference of Bayesian networks made fast and easy using an extended depth-first search algorithm

A Bayesian network is a directed acyclic graph (DAG) or a probabilistic graphical model used by statisticians. Vertices of this model represent different variables. Any connections between variables ...
WinBuzzer

Google’s TurboQuant Algorithm Slashes LLM Memory Use by 6x

Google has published TurboQuant, a KV cache compression algorithm that cuts LLM memory usage by 6x with zero accuracy loss, ...