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 ...

Google's TurboQuant algorithm compresses LLM key-value caches to 3 bits with no accuracy loss. Memory stocks fell within ...

Audio, video and data distribution can be reduced to one issue — channel capacity. The function of compression is to reduce digitized audio and video to data rates that can be supported by a channel; ...

Google has published TurboQuant, a KV cache compression algorithm that cuts LLM memory usage by 6x with zero accuracy loss, ...

Broadcasters and service providers have a wide variety of options to consider when choosing the correct compression strategy for the contribution and distribution of broadcast content. With ...

As mentioned previously, the characteristics of typical audio signals vary from time to time and therefore we must expect the required bit rate for lossless compression to vary as well. Since the bit ...

What is Google TurboQuant, how does it work, what results has it delivered, and why does it matter? A deep look at TurboQuant, PolarQuant, QJL, KV cache compression, and AI performance.

In digital video compression, using 10 bits to compress the color information in a pixel. Even though most pixels are only eight bits, the extra two bits in the compression process provides for higher ...

Because video clips are made up of sequences of individual images, or “frames,” video compression algorithms share many concepts and techniques with still-image compression algorithms. Therefore, we ...