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

A new compression technique from Google Research threatens to shrink the memory footprint of large AI models so dramatically ...

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 ...

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 ...

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 ...