assertion in 'CoSMO Semantic Post'

Full identifier: https://w3id.org/np/RAmEQd6Xc3YHZ6uH6_kOfPKx1SDVV-wn6aK8LrvcmNyZE#assertion

Assigned to 3 classes:

Minted in Nanopublication

 CoSMO Semantic Post SemanticPost Observation Claim Question comment approve/disapprove edit as derived nanopublication

This is the identifier for the assertion of this nanopublication. https://w3id.org/np/RAmEQd6Xc3...#assertion this assertion https://schema.org/keywords keywords (this is a literal) "AI" .
This is the identifier for the assertion of this nanopublication. https://w3id.org/np/RAmEQd6Xc3...#assertion this assertion https://schema.org/keywords keywords (this is a literal) "cost" .
This is the identifier for the assertion of this nanopublication. https://w3id.org/np/RAmEQd6Xc3...#assertion this assertion https://schema.org/keywords keywords (this is a literal) "initialresults" .
This is the identifier for the assertion of this nanopublication. https://w3id.org/np/RAmEQd6Xc3...#assertion this assertion https://schema.org/keywords keywords (this is a literal) "models" .
This is the identifier for the assertion of this nanopublication. https://w3id.org/np/RAmEQd6Xc3...#assertion this assertion https://schema.org/keywords keywords (this is a literal) "modelscale" .
This is the identifier for the assertion of this nanopublication. https://w3id.org/np/RAmEQd6Xc3...#assertion this assertion https://schema.org/keywords keywords (this is a literal) "scalinglaws" .
This is the identifier for the assertion of this nanopublication. https://w3id.org/np/RAmEQd6Xc3...#assertion this assertion https://schema.org/keywords keywords (this is a literal) "training" .
This is the identifier for the assertion of this nanopublication. https://w3id.org/np/RAmEQd6Xc3...#assertion The assertion above http://www.w3.org/ns/prov#wasGeneratedBy wasGeneratedBy This is a local identifier minted within the nanopublication. https://w3id.org/np/RAmEQd6Xc3...#activity activity .
This is the identifier for this whole nanopublication. https://w3id.org/np/RAmEQd6Xc3... This nanopublication date and time when the nanopublication was created http://purl.org/dc/terms/created was created on (this is a literal) "2024-09-13T18:09:57.099Z" .
This is a local identifier minted within the nanopublication. https://w3id.org/np/RAmEQd6Xc3...#sig sig http://purl.org/nanopub/x/hasSignatureTarget has as target This is the identifier for this whole nanopublication. https://w3id.org/np/RAmEQd6Xc3... this nanopublication .
This is a local identifier minted within the nanopublication. https://w3id.org/np/RAmEQd6Xc3...#sig sig http://purl.org/nanopub/x/hasAlgorithm has the algorithm (this is a literal) "RSA" .

Sensenets, 13 Sep 2024, 18:09:57 UTC

References

Nanopublication Part Subject Predicate Object Published By Published On
links a nanopublication to its assertion http://www.nanopub.org/nschema#hasAssertion assertion
assertion
Sensenets
2024-09-13T18:09:57.099Z
links a nanopublication to its assertion http://www.nanopub.org/nschema#hasAssertion assertion
assertion
Sensenets
2024-09-13T18:09:57.099Z
links a nanopublication to its assertion http://www.nanopub.org/nschema#hasAssertion assertion
assertion
Sensenets
2024-09-13T18:09:57.099Z
links a nanopublication to its provenance http://www.nanopub.org/nschema#hasProvenance provenance
assertion
Sensenets
2024-09-13T18:09:57.099Z
links a nanopublication to its provenance http://www.nanopub.org/nschema#hasProvenance provenance
assertion
Sensenets
2024-09-13T18:09:57.099Z
links a nanopublication to its assertion http://www.nanopub.org/nschema#hasAssertion assertion
assertion
Sensenets
2024-09-13T18:09:57.099Z
links a nanopublication to its provenance http://www.nanopub.org/nschema#hasProvenance provenance
assertion
Sensenets
2024-09-13T18:09:57.099Z
links a nanopublication to its assertion http://www.nanopub.org/nschema#hasAssertion assertion
assertion
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?
Sensenets
2024-09-13T18:09:57.099Z
links a nanopublication to its provenance http://www.nanopub.org/nschema#hasProvenance provenance
assertion
Sensenets
2024-09-13T18:09:57.099Z
links a nanopublication to its assertion http://www.nanopub.org/nschema#hasAssertion assertion
assertion
AI
Sensenets
2024-09-13T18:09:57.099Z

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