Previsione della comunità attuale
Sì 80%
Previsori
41
Tipo di domanda
binary
Metodologia
Play-money forecasting platform
Tipo di fonte
Previsione
Dati di mercato
Aggiornato 5 ore fa
Obsoleto12 ago 25, 00:57 UTC31 dic 35, 23:59 UTC
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Mercati Correlati
Domande correlate per il contesto, non un confronto tra contratti equivalenti.
Will a large language model beat a super grandmaster playing chess by EOY 2028?
Manifold MarketsWill a large language model beat a super grandmaster playing chess by EOY 2028?
Manifold MarketsWill a large language model beat a super grandmaster playing chess by EOY 2028?
Manifold MarketsWill a subcubic matrix multiplication algorithm be used for the primary training workload of a SOTA large-language model
Manifold MarketsWill an LLM beat a grandmaster in chess?
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Manifold MarketsRegole
This market will resolve if a chess super grandmaster is beaten in a match by a large language model before 2036.
- The point of this market is to predict if accessible LLMs will become smarter than expert humans.
- The chosen medium for this test is chess.
- Constraints:
- Human chess player must have a classical ELO of over 2700
- Human does not need to be blindfolded.
