In the early 1940s, the first tube computers began to solve problems that go beyond the capabilities of a person. Massive computers were complex, specific and generally unreliable, which makes them similar to modern quantum systems.
Like the first computers, quantum systems offer competitive advantages for companies with sufficient resources. According to analysis by Gartner, companies are currently striving to optimize processes using quantum calculations, although the superiority of quantum systems is still a subject of discussion. However, some financial institutions have already achieved certain advantages by combining classical and quantum calculations.
Large companies such as Toyota, Hyundai, and ExxonMobil have already made investments in quantum calculations, hoping to make breakthroughs in battery development, logistics optimization, and risk reduction.
Nevertheless, Gartner notes a change in priorities towards generative AI, as most executives prefer technologies with faster return on investment. Experts also emphasize the difficulties of comparing quantum systems from different suppliers due to differences in architecture and other factors.
In addition, quantum systems from different manufacturers are often optimized for specific workloads. For example, the IBM system may perform better in the field of computational chemistry, while D-Wave systems may be better suited for optimization tasks such as route planning.
Gartner argues that real progress in quantum calculations will occur when quantum algorithms are developed to solve quantum problems, which will open up new horizons for solving classes of problems that are currently inaccessible to classical computers.