If there is a subject that doesn’t need any more complexity, it is quantum computing. (See our latest guide and research on this.) We have focused our research on the main tent of quantum computing, full universal quantum, largely because it has the most disruptive potential—at least in a single bound. The reality is that despite the clamor for quantum, most enterprise leaders don’t have a clear understanding of how it works or whether the many solutions proffered by vendors are just inspired by the decades-away technology. Technology leaders must build a clear understanding of quantum, and when they do, they might find a couple of alternatives that could help with real-life problems more quickly.

So, if we can’t have quantum, what can we have?

To put it simply, there three different types of high-performance computers (see Exhibit 1) that fall into the quantum computer world (by the way, it is a bit more complicated than this—but it’s quantum, so it always will be).

Exhibit 1. The main types of “quantum” span cost, availability, and speed spectrums

Source: HFS Research, 2019

The differences between the three categories are not trivial and reach beyond cost, availability, and speed.

• Full quantum or universal quantum computers. These computers can perform the most complex of quantum algorithms, such as Shor’s and Grover’s. These quantum computers use quantum gates to build enough capacity to execute these complex calculations.
• Quantum annealing or analog quantum computers. This class of quantum computing uses analog methodologies and different quantum properties than universal quantum computers do. It’s easier to create stable workable machines using these techniques, but they have similar drawbacks to full quantum computers such as a requirement for supercooling. However, the calculations they can do are not in the same class as a full-quantum computer. They can solve some of the most complex classic computational problems (highly complex computational problems like travelling salesperson) very quickly—more than 10K-100K times faster than traditional computers, but they are not able to make a dent in full quantum algorithms like the aforementioned Shor’s and Grover’s. These analog devices will have a place in simulating quantum environments for the foreseeable future. Companies like D-Wave Systems have demonstrated that this technology is useful in some high-performance computing environments.
• Quantum “inspired” for complex computations. The benefit of these computers is not only their existence but also their reliability and their lack of special environment requirements—you can plug these computers into your existing data center. They can generate potentially large increases in speed for highly complex computational work (Fujitsu claims over 10,000 times for its Digital Annealer technology). Also, they can be programmed in a traditional manner, but they have a limiting factor in that they are focused 100% on a particular class of computational problem. This application of closer-to-real-time complex computations has great potential and gives a glimpse at what true quantum could deliver.

Even computers inspired by quantum have the power to disrupt

Frankly, it exists. It works already, and it potentially provides a real-time solution for an existing class of complicated calculations that are traditionally executed as batch tasks, such as complex resource scheduling. When the resources are factory robots, for example, this can potentially have large implications.

The uncertainty surrounding the timeframe of full quantum computing provides opportunities to intermediate technologies, particularly as their price points are significantly lower. They will have a chance to demonstrate potential use cases for disruptive step change in complex compute problem-solving. For example, a closer-to-real-time solution for the travelling salesperson problem could change the way a transportation firm implements logistics and how a manufacturing business uses its expensive factory resources. HFS has seen some initial proof of concept work with Inspired Q, where rapid computations helped maximize efficiency of various scheduled resources including vehicle fleets and factory resources.

The Bottom Line: Quantum may be a long way off, but you can enter the quantum on-ramp with potentially disruptive high-performance computing now. Complex scheduling problems for expensive resources and other highly complex computation-intensive areas such as drug design could see disruption.

In the distant future, we may be able to apply quantum technologies to real business problems. Tech leaders must recognize that quantum technology is nowhere near practical application yet. However, there is a raft of vendors pushing “quantum inspired” solutions that mimic the successes of quantum computing theory to solve real business challenges. Entering a market filling up with hype and marketing drivel, tech leaders would do well to recognize this to ensure they aren’t blind-sided by glitzy messaging and alluring use cases.