Data Compression

Byte Pair Encoding (BPE) is a data compression technique that replaces frequent pairs of bytes with a single byte.

The compression ratio is a measure of how much data is reduced in size through compression techniques.

Data compression reduces the size of data to save storage and improve transmission efficiency.

Gradient Compression reduces the size of gradient data during training to improve efficiency in distributed machine learning.

Image compression reduces the file size of images while maintaining quality, using various algorithms and techniques.

In-Context Compression refers to techniques that reduce data size while preserving context-specific information for AI model efficiency.

Lossless Compression Failure occurs when data cannot be compressed without losing information.

Middle-Out Compression is a data compression technique that optimizes both speed and efficiency by processing data from the center outward.

Mu Law Encoding is a method for compressing audio data, commonly used in telecommunication systems.

Packed Data refers to compressed data structures that optimize storage and access efficiency.

SVD Compression is a technique that reduces data size by approximating matrices using Singular Value Decomposition.