- compression ratio is defined as \( \mathrm{cmpRatio} = \mathrm{unCompressedBytes} / \mathrm{compressedBytes} \)
- Bits-per-byte is defined as \( \mathrm{compressedBits} / \mathrm{unCompressedBytes} \)
- Bits-per-byte (bpb) metric is inverse compression ratio divided by 8: \( 1 bpb = 1 / (8 \mathrm{cmpRatio}) \).
- Bits-per-character (bpc) metric for ASCII Extended characters equals bits-per-byte (bpb).
- Cross-entropy loss using log2 for a character-level language model averaged over a dataset equals bpc.
- Gzip compresses enwik8 2.92 bpb, Morse code approximately 10.8 bpc
- SRU++ model achieves 1.02 bpc - approximately compression ratio of 8

## Neural Data Compression

Data compression relies on ability to predict next symbol. Read more on neural data compression and its applications in machine learning here.