As a teenager, I was offered sage guidance by a family friend who I’d asked for advice on what to study at college. He told me that the most interesting and rewarding opportunities lie at the intersection of scientific disciplines—a thoughtful insight that has stuck with me over the decades since. In the world of deep tech, few topics generate more buzz—and confusion—than quantum computing and artificial intelligence. They’re each headline grabbers, powerful technologies in their own right and frequently misunderstood. Nevertheless, the intersection of these two fields is growing in importance and deserves serious attention from business leaders, engineers and investors. Quantum computers are often viewed as esoteric systems that operate in a vastly different way from the classical computers with which we are familiar. However, these systems actually entail a surprising amount of classical computing. Quantum computers are notoriously delicate—susceptible to noise, challenging to calibrate and they require extensive computational orchestration across a “stack” comprising multiple layers of software and hardware. This is where classical computing, and especially AI, steps in to help. Recent work demonstrated the use of classical deep learning to accelerate readout time and improve fidelity in neutral-atom-based quantum computers. Models such as these can rapidly characterize quantum states and detect system parameter drift, substantially improving performance.

Full opinion : How will the technology look like in the future when AI and quantum computing are integrated.