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  1. Mercati Predittivi
  2. IA
  3. By which date will the state-of-the-art LLM use latent space to reason?
Manifold Markets

By which date will the state-of-the-art LLM use latent space to reason?

IATecnologia2a
Manifold MarketsManifold MarketsSenza KYC
Previsione della comunità attuale
Manifold Markets
Jan 1, 2027 18.9%
In testa tra 3 esiti
Previsori

16

Tipo di domanda

multiple choice

Metodologia

Play-money forecasting platform

Tipo di fonte

Previsione

Dati di mercato

Aggiornato 9 minuti fa

9 nov 25, 5:022 gen 29, 5:01

Trend

Esito24hProbabilità

Esito scelto

Jan 1, 202719%

Regole

Meta's Coconut paper describes a new way to train AI models so that they reason in latent space.

Manifold Markets
  • Coconut doesn't have to explicitly write its thoughts in natural language (as e.g.
  • OpenAI's o1 would).
  • Abstract from the paper:
  • Large language models (LLMs) are restricted to reason in the "language space", where they typically express the reasoning process with a chain-of-thought (CoT) to solve a complex reasoning problem.
  • However, we argue that language space may not always be optimal for reasoning.

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Which of xAI, Anthropic, and OpenAI will IPO first?

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SpaceX highest valuation by end of June 2026

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Attivi in questi argomenti

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Notizie Correlate

Anthropic launches Claude Fable 5 with new safeguardsCrypto NewsEU orders Meta to restore WhatsApp access for rival AI chatbotsCrypto NewsJPMorgan plans longer-running AI agents for corporate workflows Crypto NewsOpenAI Files for IPO, Targets Valuation Up to $850BBlockchain.NewsOpenAI confidentially files to go public in the USCointelegraphNvidia expands South Korean AI partnerships across chips, cloud, and robotics Crypto News

Regole

Meta's Coconut paper describes a new way to train AI models so that they reason in latent space.

Manifold Markets
  • Coconut doesn't have to explicitly write its thoughts in natural language (as e.g.
  • OpenAI's o1 would).
  • Abstract from the paper:
  • Large language models (LLMs) are restricted to reason in the "language space", where they typically express the reasoning process with a chain-of-thought (CoT) to solve a complex reasoning problem.
  • However, we argue that language space may not always be optimal for reasoning.