The most pressing issue with quantum computing is the general public’s lack of understanding of what it can do and when it will be practical to use it. A compelling reason to pay attention to it is what it can do; it’s exciting because unlike traditional computing, which breaks problems into small steps that it can handle step by step, quantum tackles big problems all at once.
The real world is too much for digital computers
The problem with the real world is that it scales exponentially. Although conventional digital computing has become more powerful and able to tackle larger problems, it cannot scale with some of the largest computation challenges as our expectations shift and expect computing to easily handle natural language, touchless computing, “intelligent” artificial intelligence, and, ultimately, modeling the natural world. An example of the challenge is the phenomenal volume of storage required to encode the natural world. When you consider that a single human genome would take 1.5 gigabytes and that a whole human organism is 100 trillion times bigger, which translates to 150 zettabytes, it’s three or four times bigger than all the digital storage that currently exists on the planet. We can see how demands on computing are increasing both as people’s expectations of technology expand and as advanced technology’s reach includes more people. Look at Exhibit 1. It shows the increase in global internet traffic over the past two decades as the internet has grown to include both traffic from more people and more complex media.
Exhibit 1: Global internet traffic expected to expand over 3 times by 2022
Source: Cisco Visual Networking Index, 2019
You might think that something like internet traffic is finite. After all, we can only stream so many movies, right? Well, the increase in traffic occurred in conjunction with the use of new media types and new, data-intensive uses of shared networking—not to mention the cloud. The only prediction that seems likely is that data use will continue to increase exponentially as digital media becomes more real-world and realistic.
Quantum is already engaged with big problems
Nature presents the big problems that quantum can help traditional computing to solve. We have seen use cases in molecular biology, pharmaceutical organizations, materials science, and even financial services, where researchers want to use the power of quantum to tackle real-world financial ecosystem modeling. On a recent webinar, global energy company Total talked about how it is investigating the use of quantum as part of its research and development, using simulators to build models and train its team.
That is all well and good, but when will quantum be ready for prime time?
This is the big question. The answer requires a degree of trust. Researchers from academic institutions and industry are claiming big strides. Recent reports from Google claim quantum supremacy, although the practical nature of this seems far away. Ultimately, this is when the scientists look a little more sheepish because they won’t have a definitive answer until they overcome some of the current challenges. It is clear, however, that they expect to meet these challenges and that large-volume, viable, and usable levels of quantum will start to disrupt as we shift into the second intermediate stage. . Exhibit 2 shows the likely timeline.
Exhibit 2: Quantum timeline
Source: HFS Research, 2019
At the moment, we are at the “Noisy Intermediate Stage Quantum” or NISQ stage—low numbers of short-lived and noisy qubits (the building blocks for quantum). Over the next five or so years, we expect both the quality and quantity of qubits to increase. They will be able to address increasingly sophisticated algorithms faster in many cases, but they won’t be good enough to perform the most complex algorithms—this is likely to be at least a decade away. But these intermediate stages will see some disruptive use cases emerge –modelling to create new drugs and materials to simulating markets.
So what do we need to do?
We’ve said it before, and we’ll say it again: It’s all about preparation. Organizations that invest in talent and the discovery of quantum can be prepared for the next generation of hardware. Emulation and cloud versions of quantum are available for experimentation right now. We saw on our recent webinar examples of the preparation work Total are engaged in. With the firm making investment in training and quantum simulation resources for its high performance computing team. One of the challenges that quantum will be able to help with is modeling complex chemical compounds; the limits of supercomputers prevent even modeling the bonding of simple compounds.
But the biggest thing to understand about quantum computing is that it is not going to replace digital computing. Companies will use them together; digital computing will control the process from the ground up and quantum will tackle the large macro computational roadblocks. Quantum solves big problems, not small ones. If you want to be part of the first wave of disruption generated by quantum, the investment needs to happen soon.
The Bottom Line: Quantum will be a reality. Will you be a disruptor or one of the disrupted?
Taking a leaf out of Total’s book means at least look at the ways quantum could disrupt your business. It doesn’t mean wholesale hiring of physicists or data scientists (although the latter may be part of other strategic moves). It means investment in training and resources like simulators to allow researchers to investigate the use of quantum technology as part of product and service roadmaps.
