Algebraic Quantum Intelligence: A New Framework for Reproducible Machine Creativity
Kazuo Yano, Jonghyeok Lee, Tae Ishitomi, Hironobu Kawaguchi, Akira Koyama, Masakuni Ota, Yuki Ota, Nobuo Sato, Keita Shimada, Sho Takematsu, Ayaka Tobinai, Satomi Tsuji, Kazunori Yanagi, Keiko Yano, Manabu Harada, Yuki Matsuda, Kazunori Matsumoto, Kenichi Matsumura, Hamae Matsuo

TL;DR
This paper introduces Algebraic Quantum Intelligence (AQI), a novel algebraic framework inspired by quantum theory, to enhance the creative capacity of language models by expanding semantic possibilities and enabling more reproducible machine creativity.
Contribution
The paper presents AQI, a noncommutative algebraic structure integrated into transformers, to systematically expand semantic space and improve creative reasoning in language models.
Findings
AQI outperforms baseline models on creative reasoning benchmarks.
AQI reduces cross-domain variance in model performance.
AQI has been successfully deployed in real-world enterprise environments.
Abstract
Large language models (LLMs) have achieved remarkable success in generating fluent and contextually appropriate text; however, their capacity to produce genuinely creative outputs remains limited. This paper posits that this limitation arises from a structural property of contemporary LLMs: when provided with rich context, the space of future generations becomes strongly constrained, and the generation process is effectively governed by near-deterministic dynamics. Recent approaches such as test-time scaling and context adaptation improve performance but do not fundamentally alter this constraint. To address this issue, we propose Algebraic Quantum Intelligence (AQI) as a computational framework that enables systematic expansion of semantic space. AQI is formulated as a noncommutative algebraic structure inspired by quantum theory, allowing properties such as order dependence,…
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Taxonomy
TopicsMachine Learning in Materials Science · Ferroelectric and Negative Capacitance Devices · Quantum Computing Algorithms and Architecture
