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Quantum computing projects to increase 20-fold by 2023

While quantum computing is often considered to be a futuristic technology instead of a solution that can change the dynamics of IT today – research firm Gartner Inc. actually predicts that by 2023, an astounding 20 percent of organizations will be budgeting for quantum computing projects, up from less than 1 percent in 2018.

As a result, Gartner analyst Martin Reynolds stresses that quantum computing needs to become a CIO priority now as its ability to address key enterprise opportunities – and therefore drive business advantages –with the exploration of quantum inspired algorithms within specific domains.

Information Management spoke with Reynolds about what is behind the rapidly growing interest in quantum computing, and what the landscape will look like in 2023.

Information Management: I read recently that Gartner predicts that by 2023, an estimated 20 percent of organizations will be budgeting for quantum computing projects. That seems like amazing growth, considering that the percentage in 2018 was projected to be less than 1 percent. What is behind that growth?

Martin Reynolds: We are seeing the first signs that quantum computing will deliver results. The results are 5 – 10 years out, but this is like the space race. You can’t win, or even get to the finish line if you don’t start now. Quantum computing is an extraordinarily specialized discipline, and we have so much still to learn.

Also, China has promised $10B of investment, the US $1B and Europe $1e.

IM: Many people no doubt view quantum computing as some futuristic technology with little role to play now. What is the status of quantum computing in 2019?

Reynolds: We have proof that we can do proof of concept. We know how they work, we know that they can do – we just cannot yet build them at useful scale. D-Wave is generating potentially useful results, with a specialized class of quantum computer known as a quantum annealer. As a rough analog, a quantum annealer is to quantum computing as analog computers are to classical computing. As they have no program steps, they can potentially deliver useful results with relatively poor qubits. Again, though, we are in early days.

IM: For those organizations that are so-called early adopters of quantum computing, what are or will be the most common attractions?

Reynolds: The competitive advantage gained from building quantum skills and knowledge in the organization. I see the greatest opportunities coming in drug discovery and chemistry. In the early days, when quantum computers are rare, there will be breakthrough to be made in chemistry and drugs. Microsoft, for example, suggests that a catalyst could be developed that increases fertilizer production efficiency by 5%. Imagine the royalties from that. Or maybe a pharma company will find a molecule that regrows hair, or reshapes body fat.

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Working servers stand inside pod one of International Business Machines Corp.'s (IBM) Softlayer data center in Dallas, Texas, U.S. Photographer: Ben Torres/Bloomberg

So the early days, when quantum computers are rare, represent fantastic opportunities. Contrast this with, for example, better airline pricing, which requires continuous quantum computing.

IM: Are there certain industries or types of organizations that will be most drawn to quantum computing investments?

Reynolds: The biggest misunderstanding is that a quantum computer is some kind of superfast computer. It is not. It is a single-solution system where, if we can craft a problem to be solved by that solution, we can massively accelerate an answer. In most cases, collapsing something that would take thousands of years on a supercomputer into one run.

Quantum computers work on problems with small inputs and outputs, but enormous compute complexity.

Also – as a piece of trivia – quantum computers do not have an input mechanism. Any initial conditions have to be set by running code. So instead of input-compute-output, we have set up initial state – compute – output.

IM: What are some of the biggest myths and realities of quantum computing and its capabilities?

Reynolds: Quantum computer scientists and physicists are more common than we might think, but they go in to other roles. Therefore, many organizations may already have the skills needed. However, the interest in quantum computing is attracting more students at universities, so we will have a new crop of physicists coming.

There is a parallel with AI, which is characterized by new PhDs and much older long-time experts, usually in university positions.

IM: As more organizations are attracted to quantum computing deployments, what will be the impact of available skills in the marketplace to work on these projects?

Reynolds: The skill pool is shallow right now, but the interest in quantum will drive new students to it. We already see this in the relatively young staffers at the QC companies.

IM: How do data professionals and computer engineers best acquire skills with quantum computing to land these roles?

Reynolds: Acquiring these skills is extremely hard. However, the biggest problem is framing the solution, and that requires knowledge of the problem. That skill is easier to develop, and interfaces with the QC physicists. So existing IT departments will manage the part of the solution that is not quantum, making sure that the quantum physicists can help deliver the right business results.

IM: As we approach the projected 2023 target date by Gartner, how do you believe the quantum computing landscape will look different from how it does today?

Reynolds: By 2023, we should be seeing the shape of the quantum computing curve. We’ll have much richer systems, and we should be doing things that cannot be done on a conventional computer. These things most likely will not deliver business value – but will let us see what we have to do to make quantum computers successful.

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