AI

Artificiality's First Exam: An LLM-Referenced C-test for Supraintelligence

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Briefings

A new test called the C-test uses Levin's Kt to evaluate LLMs by measuring how much information is needed to represent their reasoning. Twelve LLMs were tested with items generated at high difficulty, revealing that their performance drops as difficulty increases, reaching a 'supra-intelligence' region where they can solve problems beyond current frontier intelligence.

Key points

• The C-test uses Levin's Kt, a computable variant of Kolmogorov complexity, to measure the information content required to represent LLM reasoning.
• Twelve LLMs were administered a battery of items generated at high difficulty, showing their performance decreases as difficulty increases into the supra-intelligence window.

Context

This research addresses the challenge of evaluating AI systems that may surpass current benchmarks. By using Levin's Kt, the test creates a theoretical upper bound for difficulty based on the complexity of the underlying mechanism, allowing for the certification of items before any human or frontier model can solve them.

Limitations

The study is limited to twelve LLMs and does not include human participants. Results are based on a single preprint (arXiv:2610.14005v1) and represent a first battery of certified items; the supra-intelligence window and the exact nature of the 'gap' between examiner and examinee remain unexplored.

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