12 problems
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The information-compression conjecture for mathematics and logic
The article considers mathematics, logic, and related disciplines, together with the processes of multiple alignment, unification, and search. Information-compression conjecture. M…
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The capability convergence hypothesis for machine intelligence
The paper studies machine intelligence as a system whose capabilities may depend not only on representational structure but also on access structure. Capability convergence hypothe…
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The mild-knowledge conjecture for conserved active information in AI systems
Mild-knowledge conjecture. This situation often occurs within the mild knowledge regime, so that
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Cross-context mutual-information conjecture for the exception-accumulation exponent
Let denote the exception–accumulation exponent, and let cross–context mutual information measure the information shared by a pattern across distinct contexts. Cross-contex…
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FormulaOne reasoning-depth conjecture for frontier AI models
The FormulaOne benchmark consists of algorithmic coding problems generated from Monadic Second-Order logic on graphs, with solutions requiring potentially many interdependent mathe…
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Superficial Consciousness Hypothesis for autoregressive Transformers
Let an autoregressive Transformer-based system serve as a simulated intelligence (SI), with perplexity as its base metric and the consciousness metric from Information Integration…
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The conjecture that formalizing more professional mathematics is the rate-limiting step for AI proof assistance
AI proof assistance refers to AI systems that help mathematicians develop and verify formal proofs, potentially by interacting with an interactive theorem prover. Formalization bot…
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The conjecture that AI-assisted mathematical research requires an adversarial theorem-proving process
An adversarial process is a process in which AI-generated mathematical arguments are checked by an independent formal mechanism, such as an interactive theorem prover. Interactive…
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The conjecture that natural-language-trained large language models cannot reliably reason at professional mathematics
Large language models (LLMs) are systems trained to generate text from natural-language data. Natural-language reasoning conjecture. Large language models (LLMs) trained on natural…
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Compact structured representations as a prerequisite for shareable symbolic intelligence
Structured-representation conjecture. Only on top of compact and structured representations learned by individual agents can the emergence and development of high-level intelligenc…
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The conjecture that each creative transcendence requires strictly greater intelligence
The paper considers programs that notate increasingly large ordinals, including constructions reaching beyond previously developed techniques. Intelligence-growth conjecture. Each…
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Human advantage conjecture in understanding elementary continuity proofs
Human advantage conjecture. A computer will never give an answer to questions of this type as quickly as a human because it does not know the meaning of the instructions to pick…