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Miloslav Ciz 2023-11-25 02:49:12 +01:00
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compression.md
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@ -57,7 +57,7 @@ An approach similar to the predictor may be trying to find some general mathemat
Another property of data to exploit may be its sparsity -- if for example we have a huge image that's prevalently white, we may say white is the implicit color and we only somehow store the pixels of other colors.
Some more wild techniques may include [genetic programming](genetic_programming.md) that tries to evolve a small program that reproduces the input data, or using "[AI](ai.md)" in whatever way to compress the data (in fact compression is an essential part of many [neural networks](neural_network.md) as it forces the network to "understand", make sense of the data -- many neural networks therefore internally compress and decompress the data so as to filter out the unimportant information).
Some more wild techniques may include [genetic programming](genetic_programming.md) that tries to evolve a small program that reproduces the input data, or using "[AI](ai.md)" in whatever way to compress the data (in fact compression is an essential part of many [neural networks](neural_network.md) as it forces the network to "understand", make sense of the data -- many neural networks therefore internally compress and decompress the data so as to filter out the unimportant information; [large language models](llm.md) are now starting to beat traditional compression algorithms at compression ratios).
Note that many of these methods may be **combined or applied repeatedly** as long as we are getting smaller results.