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 ...

Google has unveiled a new memory-optimization algorithm for AI inferencing that researchers claim could reduce the amount of "working memory" an AI model requires by at least 6x. As TechCrunch reports ...

Add Yahoo as a preferred source to see more of our stories on Google. On March 24, 2026 Amir Zandieh and Vahab Mirrokni from Google Research published an article on TurboQuant. TurboQuant is a ...

As AI models move from design to production, mining engineers face a double-faceted challenge: delivering real-time performance on embedded devices with ...

How lossless data compression can reduce memory and power requirements. How ZeroPoint’s compression technology differs from the competition. One can never have enough memory, and one way to get more ...

A technical paper titled “HMComp: Extending Near-Memory Capacity using Compression in Hybrid Memory” was published by researchers at Chalmers University of Technology and ZeroPoint Technologies.

For some computing components, the bottleneck to improved speed and performance hasn’t been power consumption or clock speed but physical space. But a new memory standard may provide all of the power ...

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 ...

Until now, compression algorithms such as the Lempel-Ziv-Welch (LZW) have been implemented in software. This provided acceptable compression performance in many older systems. But with today's ...