But Canadian grocery chain Save-On-Foods has become an unlikely pioneer, using quantum technology to improve the management of in-store logistics. In collaboration with quantum computing company D-Wave, Save-On-Foods is using a new type of computing, which is based on the downright weird behaviour of matter at the quantum level. And it's already seeing promising results.
The company's engineers approached D-Wave with a logistics problem that classical computers were incapable of solving. Within two months, the concept had translated into a hybrid quantum algorithm that was running in one of the supermarket stores, reducing the computing time for some tasks from 25 hours per week down to mere seconds.
Save-On-Foods is now looking at expanding the technology to other stores, and exploring new ways that quantum could help with other issues. "We now have the capability to run tests and simulations by adjusting variables and see the results, so we can optimize performance, which simply isn't feasible using traditional methods," a Save-On-Foods spokesperson tells ZDNet.
"While the results are outstanding, the two most important things from this are that we were able to use quantum computing to attack our most complex problems across the organization, and can do it on an ongoing basis."
The remarkable properties of quantum computing boil down to the behaviour of qubits -- the quantum equivalent of classical bits that encode information for today's computers in strings of 0s and 1s. But contrary to bits, which can be represented by either 0 or 1, qubits can take on a state that is quantum-specific, in which they exist as 0 and 1 in parallel, or superposition.
Qubits, therefore, enable quantum algorithms to run various calculations at the same time, and at exponential scale: the more qubits, the more variables can be explored, and all in parallel. Some of the largest problems, which would take classical computers tens of thousands of years to explore with single-state bits, could be harnessed by qubits in minutes.
The challenge lies in building quantum computers that contain enough qubits for useful calculations to be carried out. Qubits are temperamental: they are error-prone, hard to control, and always on the verge of falling out of their quantum state. Typically, scientists have to encase quantum computers in extremely cold, large-scale refrigerators, just to make sure that qubits remain stable. That's impractical, to say the least.
This is, in essence, why quantum computing is still in its infancy. Most quantum computers currently work with less than 100 qubits, and tech giants such as IBM and Google are racing to increase that number in order to build a meaningful quantum computer as early as possible. Recently, IBM ambitiously unveiled a roadmap to a million-qubit system, and said that it expects a fault-tolerant quantum computer to be an achievable goal during the next ten years.
Although it's early days for quantum computing, there is still plenty of interest from businesses willing to experiment with what could prove to be a significant development. "Multiple companies are conducting learning experiments to help quantum computing move from the experimentation phase to commercial use at scale," Ivan Ostojic, partner at consultant McKinsey, tells ZDNet.
Certainly tech companies are racing to be seen as early leaders. IBM's Q Network started running in 2016 to provide developers and industry professionals with access to the company's quantum processors, the latest of which, a 65-qubit device called Hummingbird, was released on the platform last month. Recently, US multinational Honeywell took its first steps on the quantum stage, making the company's trapped-ion quantum computer available to customers over the cloud. Rigetti Computing, which has been operating since 2017, is also providing cloud-based access to a 31-qubit quantum computer.
Another approach, called quantum annealing, is especially suitable for optimisation tasks such as the logistics problems faced by Save-On-Foods. D-Wave has proven a popular choice in this field, and has offered a quantum annealer over the cloud since 2010, which it has now upgraded to a 5,000-qubit-strong processor.
A quantum annealing processor is much easier to control and operate than the devices that IBM, Honeywell and Rigetti are working on, which are called gate-model quantum computers. This is why D-Wave's team has already hit much higher numbers of qubits. However, quantum annealing is only suited to specific optimisation problems, and experts argue that the technology will be comparatively limited when gate-model quantum computers reach maturity.
The suppliers of quantum processing power are increasingly surrounded by third-party companies that act as intermediaries with customers. Zapata, QC Ware or 1QBit, for example, provide tools ranging from software stacks to training, to help business leaders get started with quantum experiments.
In other words, the quantum ecosystem is buzzing with activity, and is growing fast. "Companies in the industries where quantum will have the greatest potential for complete disruption should get involved in quantum right now," says Ostojic.
And the exponential compute power of quantum technologies, according to the analyst, will be a game-changer in many fields. Qubits, with their unprecedented ability to solve optimisation problems, will benefit any organisation with a supply chain and distribution route, while shaking up the finance industry by maximising gains from portfolios. Quantum-infused artificial intelligence also holds huge promise, with models expected to benefit from better training on bigger datasets.
One example: by simulating molecular interactions that are too complex for classical computers to handle, qubits will let biotech companies fast-track the discovery of new drugs and materials. Microsoft, for example, has already demonstrated how quantum computers can help manufacture fertilizers with better yields. This could have huge implications for the agricultural sector, as it faces the colossal task of sustainably feeding the growing global population in years to come.
Chemistry, oil and gas, transportation, logistics, banking and cybersecurity are often cited as sectors that quantum technology could significantly transform. "In principle, quantum will be relevant for all CIOs as it will accelerate solutions to a large range of problems," says Ostojic. "Those companies need to become owners of quantum capability."
There is a caveat. No CIO should expect to achieve too much short-term value from quantum computing in its current form. However fast-growing the quantum industry is, the field remains defined by the stubborn instability of qubits, which still significantly limits the capability of quantum computers.
"Right now, there is no problem that a quantum computer can solve faster than a classical computer, which is of value to a CIO," insists Heike Riel, head of science and technology at IBM Research Quantum Europe. "But you have to be very careful, because the technology is evolving fast. Suddenly, there might be enough qubits to solve a problem that is of high value to a business with a quantum computer."
And when that day comes, there will be a divide between the companies that prepared for quantum compute power, and those that did not. This is what's at stake for business leaders who are already playing around with quantum, explains Riel. Although no CIO expects quantum to deliver value for the next five to ten years, the most forward-thinking businesses are already anticipating the wave of innovation that the technology will bring about eventually -- so that when it does, they will be the first to benefit from it.
This means planning staffing, skills and projects, and building an understanding of how quantum computing can help solve actual business problems. "This is where a lot of work is going on in different industries, to figure out what the true problems are, which can be solved with a quantum computer and not a classical computer, and which would make a big difference in terms of value," says Riel.
Riel points to the example of quantum simulation for battery development, which companies like car manufacturer Daimler are investigating in partnership with IBM. To increase the capacity and speed-of-charging of batteries for electric vehicles, Daimler's researchers are working on next-generation lithium-sulfur batteries, which require the alignment of various compounds in the most stable configuration possible. To find the best placement of molecules, all the possible interactions between the particles that make up the compound's molecules must be simulated.
This task can be carried out by current supercomputers for simple molecules, but a large-scale quantum solution could one day break new ground in developing the more complex compounds that are required for better batteries.
"Of course, right now the molecules we are simulating with quantum are small in size because of the limited size of the quantum computer," says Riel. "But when we scale the next generation of quantum computers, then we can solve the problem despite the complexity of the molecules."
Similar thinking led oil and gas giant ExxonMobil to join the network of companies that are currently using IBM's cloud-based quantum processors. ExxonMobil started collaborating with IBM in 2019, with the objective of one day using quantum to design new chemicals for low energy processing and carbon capture.
The company's director of corporate strategic research Amy Herhold explains that for the past year, ExxonMobil's scientists have been tapping IBM's quantum capabilities to simulate macroscopic material properties such as heat capacity. The team has focused so far on the smallest of molecules, hydrogen gas, and is now working on ways to scale the method up to larger molecules as the hardware evolves.
A number of milestones still need to be achieved before quantum computing translates into an observable business impact, according to Herhold. Companies will need to have access to much larger quantum computers with low error rates, as well as to appropriate quantum algorithms that address key problems.
"While today's quantum computers cannot solve business-relevant problems -- they are too small and the qubits are too noisy -- the field is rapidly advancing," Herhold tells ZDNet. "We know that research and development is critical on both the hardware and the algorithm front, and given how different this is from classical computing, we knew it would take time to build up our internal capabilities. This is why we decided to get going."
Herhold anticipates that quantum hardware will grow at a fast pace in the next five years. The message is clear: when it does, ExxonMobil's research team will be ready.
One industry that has shown an eager interest in quantum technology is the financial sector. From JP Morgan Chase's partnerships with IBM and Honeywell, to BBVA's use of Zapata's services, banks are actively exploring the potential of qubits, and with good reason. Quantum computers, by accounting for exponentially high numbers of factors and variables, could generate much better predictions of financial risk and uncertainty, and boost the efficiency of key operations such as investment portfolio optimisation or options pricing.
Similar to other fields, most of the research is dedicated to exploring proof-of-concepts for the financial industry. In fact, when solving smaller problems, scientists still run quantum algorithms alongside classical computers to validate the results.
"The classical simulator has an exact answer, so you can check if you're getting this exact answer with the quantum computer," explains Tony Uttley, president of Honeywell Quantum Solutions, as he describes the process of quantum options pricing in finance.
"And you better be, because as soon as we cross that boundary, where we won't be able to classically simulate anymore, you better be convinced that your quantum computer is giving you the right answer. Because that's what you'll be taking into your business processes."
Companies that are currently working on quantum solutions are focusing on what Uttley calls the "path to value creation". In other words, they are using quantum capabilities as they stand to run small-scale problems, building trust in the technology as they do so, while they wait for capabilities to grow and enable bigger problems to be solved.
Tempting as it might be for CIOs to hope for short-term value from quantum services, it's much more realistic to look at longer timescales, maintains Uttley. "Imagine you have a hammer, and somebody tells you they want to build a university campus with it," he says. "Well, looking at your hammer, you should ask yourself how long it's going to take to build that."
Quantum computing holds the promise that the hammer might, in the next few years, evolve into a drill and then a tower crane. The challenge, for CIOs, is to plan now for the time that the tools at their disposal get the dramatic boost that's expected by scientists and industry players alike.
It is hard to tell exactly when that boost will come. IBM's roadmap announces that the company will reach 1,000 qubits in 2023, which could mark the start of early value creation in pharmaceuticals and chemicals, thanks to the simulation of small molecules. But although the exact timeline is uncertain, Uttley is adamant that it's never too early to get involved.
"Companies that are forward-leaning already have teams focused on this and preparing their organisations to take advantage of it once we cross the threshold to value creation," he says. "So what I tend to say is: engage now. The capacity is scarce, and if you're not already at the front of the line, it may be quite a while before you get in."
Creating business value is a priority for every CIO. At the same time, the barrier to entry for quantum computing is lowering every time a new startup emerges to simplify the software infrastructure and assist non-experts in kickstarting their use of the technology. So there's no time to lose in embracing the technology. Securing a first-class spot in the quantum revolution, when it comes, is likely to be worth it.