Google’s TurboQuant has the internet joking about Pied Piper from HBO's "Silicon Valley." The compression algorithm promises ...

Google’s TurboQuant could cut LLM memory use sixfold, signaling a shift from brute-force scaling to efficiency and broader AI ...

The biggest memory burden for LLMs is the key-value cache, which stores conversational context as users interact with AI chatbots. The cache grows as conversations lengthen, ...

Suffix arrays serve as a fundamental tool in string processing by indexing all suffixes of a text in lexicographical order, thereby facilitating fast pattern searches, text retrieval, and genome ...

Google's TurboQuant combines PolarQuant with Quantized Johnson-Lindenstrauss correction to shrink memory use, raising ...

Within 24 hours of the release, community members began porting the algorithm to popular local AI libraries like MLX for Apple Silicon and llama.cpp.

With TurboQuant, Google promises 'massive compression for large language models.' ...

Google thinks it's found the answer, and it doesn't require more or better hardware. Originally detailed in an April 2025 paper, TurboQuant is an advanced compression algorithm that’s going viral over ...

Microsoft is open-sourcing its cloud-compression algorithm and optimized hardware implementation for cloud storage. Microsoft is contributing that algorithm, known as ""=""> plus the associated ...

Effective compression is about finding patterns to make data smaller without losing information. When an algorithm or model can accurately guess the next piece of data in a sequence, it shows it’s ...

The amount of data that the big cloud computing providers now store is staggering, so it’s no surprise that most store all of this information as compressed data in some form or another — just like ...