Infosys has integrated aspects of quantum computing to its current implementations of optimization problems, machine learning, and cybersecurity. Infosys uses a hybrid approach to implement aspects of quantum within a traditional computing environment. Using this approach Infosys will be prepared when quantum computing becomes broadly available:
“While classical algorithms are effective in many domains, they can be prohibitively slow and expensive when it comes to solving certain kinds of optimization problems. For example, in finance, it is difficult to use traditional computers to optimize portfolios, since this necessitates rapid, real-time analysis of the constantly fluctuating risk values associated with investing in each individual stock. To address this challenge, Infosys developed quantum-inspired algorithms to optimize the selection and allocation of assets. This enabled the company to build a diversified portfolio that maximized returns and minimized risks for more than 100 stocks in just one minute, ultimately achieving a 21% improvement in returns compared to conventional (i.e., non-quantum-inspired) asset allocation strategies.
Another area in which traditional computers can struggle to optimize accurately and cost-effectively is in supply chain. To explore the potential for quantum computing in this space, Infosys partnered with QpiAI, a startup developing quantum-inspired solutions for supply chain optimization. While these projects are still in development, the team has already shown that its algorithms enable a 60% cost reduction in vehicle routing optimization.”
Overview by Tim Sloane, VP, Payments Innovation at Mercator Advisory Group