Nanopublications

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    a np:Nanopublication .
}

sub:assertion {
  sub:assertion dcterms:creator <https://w3id.org/np/RAoSadUw99CeqDlR2400018nqTzR_38fT86OrTzk16Vts> ;
    a schema:Claim , schema:Observation , schema:Question ;
    rdfs:comment """ 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?

""" ;
    schema:keywords "AI" , "cost" , "initialresults" , "models" , "modelscale" , "scalinglaws" , "training" .
}

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    dcterms:creator <https://w3id.org/np/RAoSadUw99CeqDlR2400018nqTzR_38fT86OrTzk16Vts> ;
    dcterms:license <https://creativecommons.org/licenses/by/4.0/> ;
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    rdfs:label "CoSMO Semantic Post" ;
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    foaf:name "Leshem Choshen 🤖🤗 @ICML wanna talk?" .
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