Comment by Hasz
2 hours ago
I really like the idea that compression is intelligence, there are so many tricks an interesting ideas related to it. A bunch of them are described in the article, but you can imagine a long tail of many more inscrutable tricks chained together to get really incredible shrinkage in data.
Hutter prize (I think mentioned in a 3b1b video somewhere else in this thread) is a great example. Given this was written before advent of LLM, I would love to see someone throw openAI/Anthropic levels of compute at a similar problem to see what the swarm can produce.
The newest submissions to Hutter Prize made crazy jumps by just replacing the LSTM with a transformer and training it.
35'000$ for a prompt and some training is a nice chunk of cash.
Next steps are replacing the encoders and all the other human-biased compression parts by just raw data and training, probably another 20-30% is up for grabs.
I remember reading an article on here by one of the founders of MPEG about why he was leaving MPEG after several decades, and part of it was that modern AI is indistinguishable from compression and he wanted to explore new compression algorithms using the recent explosion of knowledge