Google Research released TurboQuant, a training-free compression algorithm that can compress the KV cache of large language ...

Compression algorithms for speech, audio, still images, and video are quite complicated and, more importantly, nearly always lossy. Thus, samples often change dramatically once they’re decompressed.

Running a large language model is expensive, and a surprising amount of that cost comes down to memory, not computation.

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.

The goal of digital compression algorithms is to produce a digital representation of an audio signal which, when decoded and reproduced, sounds the same as the original signal, while using a minimum ...

Compression reduces bandwidth and storage requirements by removing redundancy and irrelevancy. Redundancy occurs when data is sent when it’s not needed. Irrelevancy frequently occurs in audio and ...

Algorithm promises faster data transfer speeds and reduced Web page load times by compressing content up to 8 percent smaller than zlib. Steven Musil is a senior news editor at CNET News. He's been ...

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 ...