Full identifier: https://w3id.org/np/RAmEQd6Xc3YHZ6uH6_kOfPKx1SDVV-wn6aK8LrvcmNyZE#assertion
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links a nanopublication to its provenance
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links a nanopublication to its assertion
http://www.nanopub.org/nschema#hasAssertion
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links a nanopublication to its provenance
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links a nanopublication to its assertion
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Scaling laws don't care about scale of the "train" models?
Did anyone else get this?
When I predict a scaling law, the scale of the largest model matters, but the num-models for fitting matters much much much more.
Initial results, scaling error by #models starting from largest https://twitter.com/LChoshen/status/1803401845626511568/photo/1
Maybe more simply put:
You can predict a scaling law with 8 small models, and it would be better than 3 large ones (that costs a lot)
Is that something anyone else seen?
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links a nanopublication to its provenance
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links a nanopublication to its assertion
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AI
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