Large-scale applications, such as generative AI, recommendation systems, big data, and HPC systems, require large-capacity ...

At 100 billion lookups/year, a server tied to Elasticache would spend more than 390 days of time in wasted cache time.

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

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 ...

TurboQuant compresses AI model vectors from 32 bits down to as few as 3 bits by mapping high-dimensional data onto an efficient quantized grid. (Image: Google Research) The AI industry loves a big ...

Nvidia researchers have introduced a new technique that dramatically reduces how much memory large language models need to track conversation history — by as much as 20x — without modifying the model ...

Nabsys and the Research Lab of Dr. Martin Taylor, Brown University, Present Data Using the OhmX™ Platform at AGBT 2026 EGM enables the direct detection of endonuclease activity at the genome scale by ...

There are one instrumented test and one local test in the project. Open it on Android Studio or IntelliJ and run them.

Researchers have created a protein that can detect the faint chemical signals neurons receive from other brain cells. By tracking glutamate in real time, scientists can finally see how neurons process ...