I am also @[email protected]
This is not new knowledge and predates the current LLM fad.
See the Hutter prize which has had “machine learning” based compressors leading the ranking for some time: http://prize.hutter1.net/
It’s important to note when applied to compressors, the model does produce a code (aka encoding) that exactly reproduces the input. But on a different input the same model is unlikely to produce an impressive compression.
Just switch to the F-Droid version.
Better: make sure all the apps you use come from F-Droid
“Starch based” plastic is just a way to greenwash PLA.
Just because the C, H, and O originally came from starch, does not automatically make the chemically synthesized product safe.
They do this to juice the gross margin number and make the auto business appear more profitable.
Haha…yes fair enough. I changed the truck’s oil.
I could have said it better.
I mean compressor as half of a compression/decompression algorithm. The better way I should have worded it is: when you apply machine learning to a compression problem, you can do it lossless…your uncompressed output will be identical to the input, every time.
“NNCP” is a good search term to learn more, specifically about how this works.