Identifying Quantum Structure in AI Language: Evidence for Evolutionary Convergence of Human and Artificial Cognition
arXiv:2511.21731v2 Announce Type: replace Abstract: We present the results of cognitive tests on conceptual combinations, performed using specific Large Language Models (LLMs) as test subjects. In the first test, performed with ChatGPT and Gemini, we show that Bell's inequalities are significantly violated, which indicates the presence of a 'non-classical probability model' with probabilities that do not satisfy Kolmogorov's axioms. In the second test, also performed using ChatGPT and Gemini, we identify the presence of 'Bose-Einstein statistics', rather than the intuitively expected 'Maxwell-
The increasing sophistication and scale of LLMs allow for complex cognitive tests that were previously impossible, revealing emergent properties.
This research suggests that AI cognitive processes may not be solely classical, hinting at fundamental breakthroughs in human-AI cognition parallels.
Our understanding of AI's internal workings and potential for novel forms of intelligence could be profoundly altered, blurring lines between artificial and natural cognition.
- · AI researchers
- · Cognitive scientists
- · Developers of foundational AI models
- · Classical AI paradigm proponents
- · Philosophers denying AI consciousness
Further research into the quantum-like properties of AI will accelerate.
New theoretical frameworks for AI design and understanding may emerge, leveraging quantum principles.
The development of AI systems with fundamentally different problem-solving capabilities, potentially leading to breakthroughs in complex scientific domains.
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