Beyond the Hype: Hybrid Quantum-Classical AI Agents for Scientific Discovery – A Benchmark-Driven Reality Check

This talk explores the emerging potential of hybrid quantum-classical AI agents, combining technologies like LLMs with QNNs or QRL. Focusing on real-world applications such as materials science, Robotics, and CAE, we present methodological development and PoCs that highlight where Quantum Machine Learning offers advantages or not compared to classical ML and AutoML methods. By examining concrete use cases, we address the critical question: Is Quantum AI already useful, or still just theoretical? The session offers a grounded, realistic view of quantum’s role in the future of AI.