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 ...

Even if you don’t know much about the inner workings of generative AI models, you probably know they need a lot of memory. Hence, it is currently almost impossible to buy a measly stick of RAM without ...

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.” ...

This voice experience is generated by AI. Learn more. This voice experience is generated by AI. Learn more. I have written in March about Google’s TurboQuant for compressing data in memory for AI ...

As Large Language Models (LLMs) expand their context windows to process massive documents and intricate conversations, they encounter a brutal hardware reality known as the "Key-Value (KV) cache ...

Google Research's TurboQuant memory-compression algorithm has raised concerns that demand for AI-related memory could weaken, but South Korean experts and analysts say the market reaction may be ...

More software solutions to the hardware crisis are on their way ...

Lossless compression is used for applications where the original data must be fully restored following decompression. Examples of applications requiring lossless compression include network data, ...

Sponsored Feature: Computers are taking over our daily tasks. For big tech, this means an increase in IT workloads and an expansion of advanced use cases in areas like artificial intelligence and ...

I have written in March about Google’s TurboQuant for compressing data in memory for AI applications, focusing on data center applications. In that article, I said that TurboQuant is a compression ...