Google Research unveiled TurboQuant, a novel quantization algorithm that compresses large language models’ Key-Value caches ...

A research team has developed a Gaussian Splatting processing platform that supports end-to-end processing from data acquisition to multi-platform rendering. Their framework provides a solid ...

To meet the quality compliance requirements of Tier-1 global clients such as Apple and Tesla, relevant data must be retained for periods ranging from 6 months to 15 years to ensure end-to-end ...

Nvidia (NASDAQ: NVDA) is showing signs of renewed momentum and a potential breakout after an extended period of consolidation ...

Large language models (LLMs) aren’t actually giant computer brains. Instead, they are massive vector spaces in which the ...

Artificial intelligence model compression startup Refiant AI said today it has raised $5 million in seed funding from VoLo Earth Ventures to try to put an end to the “arms race” that has ignited a ...

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

Memory prices are plunging and stocks in memory companies are collapsing following news from Google Research of a breakthrough that will greatly reduce the amount of memory needed for AI processing.

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.

If Google’s AI researchers had a sense of humor, they would have called TurboQuant, the new, ultra-efficient AI memory compression algorithm announced Tuesday, “Pied Piper” — or, at least that’s what ...

Google (GOOG)(GOOGL) revealed a set of new algorithms today designed to reduce the amount of memory needed to run large language models and vector search engines. The algorithms introduced by Google ...