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 ...
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.

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 ...
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 ...

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 ...

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.
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, ...
Nanowerk

Researchers create an algorithm that maximizes IoT sensor inference accuracy using edge computing

(Nanowerk News) We are in a fascinating era where even low-resource devices, such as Internet of Things (IoT) sensors, can use deep learning algorithms to tackle complex problems such as image ...