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bob1029today at 7:53 AM3 repliesview on HN

Not without attention or something approximating it.

The fact that gzip is relatively fast should be your first clue that something important is missing.

Gzip is great at predicting the next token for one very specific narrative. LLMs can predict next tokens for entire universes of narratives. Searching for the correct next token across this space scales ~quadratically with the input size. Gzip scales linearly. I can gzip a one terabyte file. Imagine feeding that much into an LLM. These are wildly different animals that happen to overlap in a very small way. Equating compression to intelligence looks increasingly silly to me.

If we must compare language models to compression, they are much more like jpeg and mp3 than they are gzip and flac. I can go fuck with a jpeg file pretty severely at the bitstream level and still have something resembling performance on the other side. Gzip cannot remotely approach this.


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Retr0idtoday at 8:04 AM

> Gzip scales linearly. I can gzip a one terabyte file.

In part because gzip only has a 32KiB window size, and I think it'd be at least quadratic within that window if you were going for optimal compression.

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fedeb95today at 8:28 AM

I agree, but also equating LLMs with intelligence is wrong.

ameliustoday at 7:56 AM

Perhaps a better question is if LLMs are used as compressors, how well is that expected to work.

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