Making quantum computing a reality
While quantum computers exist in the laboratory, general-purpose quantum computers are not yet available for commercial use. How can companies respond to potential disruptions to this technology before it hits the mainstream market? One company that has invested heavily in quantum computing is Infosys, so the authors contacted several researchers and business leaders within the company to learn more about their work. They found that Infosys took a hybrid approach, blending elements of classical and quantum computing to build a bridge between today’s reality and tomorrow’s disruptive technologies. This has helped the company advance in harnessing quantum technology in a variety of applications, including optimization problems, machine learning, and cybersecurity. Although there is still a long way to go in the development and application of quantum technology, a hybrid approach allows companies to serve their customers today, while being one step ahead of the future. , although some of the technologies involved are still catching up.
Scientists have theorized about the potential of quantum computing — that is, a new approach to computation that uses probabilities, rather than binary signals, to perform calculations — for decades. But in recent years, private and public sector investment in the development of quantum computers has increased dramatically, with a report planning investments of more than $800 million in 2021 alone.
Quantum technology could revolutionize everything from genomic sequencing to optimizing transport pathways, from decoding to the development of new materials. But while quantum computers exist in the lab, general-purpose quantum computers are not yet available for commercial use. How can companies respond to potential disruptions to this technology before it hits the mainstream market?
To explore this question, it is useful to look at historical examples of major technological transitions, such as the shift from analog photography to digital photography, or from internal combustion to electric motors. In many of these cases, companies have taken advantage of a hybrid approach to integrating new technologies: rather than trying to switch to new technology all at once, they have developed products that combine elements of old and new technologies. For example, the hybrid-electric Prius allowed Toyota to learn how to make electric cars while leveraging its core expertise with traditional gasoline engines. After launching that first hybrid model, Toyota moved forward with plug-in hybrid cars and fuel cell electric cars, paving the way for its eventual launch of all-electric cars several years later.
So what might a similar hybrid approach for quantum computing look like? One organization that has invested heavily in quantum computing is Infosys, so we reached out to several researchers and business leaders at the company to learn more about their work. Through a series of in-depth interviews, we discovered that Infosys had experimented with two hybrid approaches to begin to commercialize existing innovations and bridge the future of quantum computing:
- Quantum-inspired algorithms: algorithms that run on classical computers, but whose logic is based on the emulation of various quantum phenomena (unlike the binary, deterministic approach of traditional computing)
- Hybrid models: models that allow classical computers to work with quantum computers
Infosys has leveraged these approaches in many different areas, both independently and in partnership with startups. Below, we describe three key applications of quantum computing that Infosys has begun to invest in: optimization problems, in which the company has explored the potential of quantum-inspired algorithms, and machine learning solutions. and cybersecurity, where Infosys has begun to take advantage of hybrid models. .
Although classical algorithms are effective in many areas, they can be extremely slow and expensive when it comes to solving certain types of optimization problems. For example, in finance, it is difficult to use traditional computers to optimize portfolios because it requires rapid, real-time analysis of the constantly fluctuating risk values associated with investing in each individual stock. To meet this challenge, Infosys has developed quantum-inspired algorithms to optimize asset selection and allocation. This allowed the firm to construct a diversified portfolio that maximized returns and minimized risk for over 100 stocks in just one minute, ultimately achieving a 21% improvement in returns compared to conventional asset allocation strategies. (i.e. not quantum-inspired).
Another area where traditional computers can struggle to optimize accurately and cost-effectively is supply chain. To explore the potential of quantum computing in this space, Infosys has 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 lead to a 60% reduction in vehicle routing optimization costs.
Machine learning algorithms depend on very intensive (and expensive) computing power to extract learnings from large datasets. Especially when it comes to analyzing very unbalanced datasets – i.e. when the cases you care to identify are extremely rare – quantum computing could both significantly reduce costs and improve the efficiency of these models.
In the detection of financial fraud, for example, the number of fraudulent transactions is tiny compared to the number of normal transactions. It is therefore difficult to develop classical machine learning algorithms capable of identifying fraud sufficiently quickly and accurately. But Infosys took a hybrid approach, creating a hybrid neural network algorithm in which most network layers used classical computing, while some layers incorporated input from a quantum computer. Thanks to this system, Infosys was able to achieve a 1.66% improvement in the accuracy of its fraud detection tool – a difference that may seem small, but could translate into significant savings given the massive scale of the global financial system.
Current cybersecurity protocols typically use pseudo-random numbers to encrypt sensitive information such as passwords, personal data, or even blockchains. The problem is that quantum computers can easily crack the methods used by traditional computers to generate random numbers, potentially posing a huge threat to any organization using these standard encryption tools. Yet alongside this new threat, quantum technology also offers new possibilities: quantum systems can produce a large and reliable stream of “true random“numbers that cannot be deciphered with classical or quantum systems.
Infosys partners with quantum cybersecurity firm Quintessence Laboratories to develop a hybrid solution that first generates real random keys with a quantum random number generator, then funnels those keys into cryptographic algorithms and classic ciphers. This approach makes it possible to generate truly random and unpredictable numbers for use in a wide variety of existing business applications, enabling a new level of cybersecurity for any organization working with large amounts of sensitive data.
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These apps may sound like science fiction, but they are real. While quantum computers still have a long way to go before they are ready for prime time, companies are already leveraging quantum technologies in hybrid solutions, blending the old and the new to build a bridge between today’s reality and tomorrow’s potential. Investing in this hybrid strategy is now the best way for companies to develop the expertise in quantum principles and software development that will become critical as these technologies mature. It also means that regardless of exactly how quantum hardware develops and which platforms eventually become industry standards, the algorithms developed today will be able to run on almost any type of quantum hardware (rather than being limited to one system). Ultimately, adopting a hybrid approach allows companies to serve their customers today, while being one step ahead of the future, even if some of the technology involved is still in the process of being developed. catch up.