Unlike AI, which has driven a surge in demand for graphics processors to train and run large language models, quantum computing targets a different class of challenges. Researchers say the technology could accelerate molecular simulations, optimize complex logistics networks, advance materials science and improve cryptography.
Krishna said IBM has already demonstrated some of that potential, using quantum computers to uncover properties of materials that conventional computers had been unable to model. Those insights could eventually contribute to longer-lasting batteries, new materials, fusion energy research and drug discovery.
Growing confidence around commercialization has been matched by rising investment. In May, IBM announced plans for a standalone quantum chip foundry backed by a $1 billion commitment from the U.S. Department of Commerce through the CHIPS incentive program, alongside a matching $1 billion investment from the company. Other developers have also expanded manufacturing capacity and research partnerships as they push toward fault-tolerant quantum computers.
The industry’s progress is also drawing attention from the digital asset sector. Several publicly traded bitcoin miners, including MARA Holdings (MARA), Riot Platforms (RIOT) and CleanSpark (CLSP), have diversified into AI and high-performance computing, leveraging their data centers and power infrastructure for new computing workloads.
Quantum computers won’t simply slot into today’s AI data centers. They require entirely different hardware and operating environments, meaning the industry will need new facilities and supply chains as the technology matures.
