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LarsDu88 • today at 6:14 PM • 3 replies • view on HN

Intuitively this makes sense. When you have small models, they need to compress more by leveraging superposition and polysemanticity.

Nick is looking at a 32B model, which certainly has to compress less... Now we have 10 trillion parameter models... do they need to compress at all? As far as I can tell, experiments show that Fable has basically memorized every lat/long position on the map of the earth can can tell you at a glance whether your standing in the ocean or not based on your coordinates


Replies

teruakohatu • today at 6:35 PM

> far as I can tell, experiments show that Fable has basically memorized every lat/long position on the map of the earth … your standing in the ocean or not based on your coordinates

Memorising a small shape file of the earth’s continents can allow you to determine if a person is on land or in water.

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bschne • today at 6:31 PM

where's this specific example/experiment from? curious to read more, never heard of this

soulofmischief • today at 6:37 PM

All functional knowledge is compression and contextual decompression. Sometimes this compression can be lossless or nearly so. Compression doesn't automatically mean loss of information.