Q GPT: A New Direction in Quantum AI Integrating Large Language Models with Quantum Optimization for Accelerated Industrial Problem Solving

As industries increasingly encounter complex optimization challenges, the convergence of Artificial Intelligence (AI) and Quantum Computing offers a promising pathway to scalable, efficient solutions. This work proposes a novel framework — including the introduction of Q GPT, a purpose-built AI system designed to solve complex optimization problems using quantum resources — that integrates Large Language Models (LLMs) with Quantum Optimization techniques to bridge the gap between classical and quantum paradigms in industrial applications. LLMs, with their advanced reasoning and language capabilities, serve as intelligent interfaces that translate high‑level industrial problems into quantum‑compatible formulations such as Ising or QUBO models. These formulations are then processed using state‑of‑the‑art quantum optimization algorithms, including quantum annealing and variational approaches. By combining the semantic understanding of LLMs with the computational power of quantum systems, this hybrid approach significantly reduces the overhead for domain experts in accessing quantum technologies. We explore architectural designs, use cases in logistics and energy, and the potential of this synergy to accelerate decision‑making, lower cost barriers, and foster broader quantum adoption in real‑world industrial settings.