Humanity's Final Conjecture: Evaluation of AI Innovation Capability Based on Prime Number Distribution
Year: 2025
Type: article
Abstract: As Large Language Models (LLMs) saturate traditional benchmarks, existing evaluations fail to distinguish between knowledge reproduction and source innovation. This paper proposes the "Innovation Turing Test," a paradigm designed to assess the divergent thinking and abductive reasoning essential for scientific discovery. We construct an open-ended test case, the "Prime-Chaos Conjecture," which requires models to bridge Peano arithmetic and symbolic dynamics. The task involves demonstrating that prime pseudorandomness manifests as low-dimensional deterministic chaos and deriving the Logistic map's topological properties at the band merging point ($u \approx 1.5437$). We detail a scalable human-AI collaborative evaluation method and present empirical results from models like Gemini and Qwen. Notably, Gemini successfully identified physical concepts such as the "Effective Horizon". This study aims to provide a quantitative yardstick for the transition of AGI from "Problem Solvers" to "Researchers".
Author: wang, liang
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7109637752
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