@Hesamation: 3Blue1Brown’s new video explains why every LLM is actually a compression machine. everyone describes pre-training as “n…
Summary
3Blue1Brown's new video explains that LLMs are fundamentally compression machines, linking next-token prediction to efficient encoding of human knowledge, which leads to better abstraction and reasoning.
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3Blue1Brown’s new video explains why every LLM is actually a compression machine.
everyone describes pre-training as “next token prediction” but that’s just the surface-level objective.
in reality it is a means to making the most efficient text compressor.
prediction and compression are two sides of the same coin.
when you train the model to predict the next token you’re not just teaching it to guess the next word but how to best encode the human knowledge it sees.
better compression means better abstraction means better reasoning
at some point, compression stops looking like storage or a database (as some like to call it on X) and looks like an approximation of understanding.
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