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

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 ...

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, ...

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 ...

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 ...

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.

Video compression was one of the more ubiquitous topics at last month’s NAB Show. Perhaps equally ubiquitous was 4K and 8K. Seldom was one of either topic discussed without reference to the other.