Progress is steady, but the technology hasn’t matured enough for most enterprises to truly benefit. Here’s what needs to happen.
Eyes are fixed on quantum computing. The president recently announced a goal to double AI spending and quantum computing R&D. Major technology vendors have taken steps to make quantum computers and simulators available to developers to jumpstart the creation of real-world quantum computing applications.
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Quantum’s sheer computing power to help solve society’s biggest challenges across industries is indisputable. But what about enterprises? Amidst all the quantum noise, how does an organization know if it should apply — or even test — the technology against its goals and challenges? Before we answer those questions, it’s important to consider the maturity of quantum computers today and factors that will speed it up.
Commercial viability
In a 2019 study, BCG concluded that it will be another 10 to 20 years before quantum computers are expected to achieve superior performance in “tasks of genuine industrial significance,” such as R&D for chemicals. To get close to that place, the technology needs to significantly advance.
What’s already been achieved is amazing. Quantum equations were born from 20th century speculation on the mechanics of the universe at subatomic levels. Quantum computing is taking those principles and building a machine around them for everyday business use. To do that, researchers aren’t just inventing the hardware, but the operating system and programming layers, too.
With major technology players announcing quantum services, it’s easy to feel like a feasible quantum computer for practical applications is just around the corner. But is it?
In this instance, feasibility denotes a development system that’s both accessible and delivers life-changing results. To get a sense for the mileage left until feasibility for quantum computing, consider the time between ENIAC and IBM 360. ENIAC was the first electronic digital computer. Everything about it had to be invented. System 360 was the first general programmable computer. It hit the market about 19 years after ENIAC. If the first D-Wave came out 9 years ago, will it be another 10 years before we see the feasible quantum version of the IBM 360?
While it may very well be less time than that, as with the IBM 360, there will be decades of innovation after a feasible release to render it accessible to the masses. Some firms and agencies, probably in cryptography, will make immediate gains. The rest will accelerate steadily, but slowly. Businesses will hedge their bets on the best time for quantum market entry.
Prioritize education and training
Past isn’t a prologue for every aspect of quantum. Innovation spreads faster now in a world with open source technology, online learning, crowdsourcing and hybrid development environments. Users and potential stakeholders expect collaborative gains. Advancing quantum computing will require developers to have tangible opportunities to learn and test the technology, so they can eventually start creating viable applications for commercial use.
IBM, Google and Microsoft offer products for learning where developers can practice building applications visually, write the code and do test runs on actual hardware. It’s that actual hardware from providers like Fujitsu, IBM and AWS that feels most promising: It’ll allow citizen users to form an impression of both what’s possible now and is yet to be defined.
The quantum price tag is high, so true value acceleration will happen when the hardware is affordable and accessible.
Should my enterprise consider quantum?
The most immediate applications will come to enterprises with lots of data. Some banks and airlines are already testing quantum algorithms on both qubit architecture and simulators with the large tech vendors. Pharmaceuticals are starting to engage the next generation of researchers on quantum architecture.
The COVID-19 outbreak has certainly focused attention on quantum’s promise for accelerating viral protein research through simulations. The IBM Summit supercomputer was used in January to process a short-list of vaccine test molecule candidates in two days. Quantum would be able to do that in minutes.
For hedge funds and insurance firms, quantum can speed the simulations and forecasting models of today. This will allow firms to speculate with ever larger datasets, each requiring less effort to groom, and experimentally surface correlations between variables that are monetizable but too costly to find with classical techniques today.
As for platform vendors, CRM systems gain access to more data each year that can be correlated with buyer behavior. In the advertising and social media industries, quantum-based platforms will be able to process incredibly large variable counts to seek unprecedented product/service matches.
Other treasures will be found as the technology is applied, developers are properly trained, and users continue to ask questions. Realistically, by the time quantum is feasible, most enterprises outside of R&D can expect to simply inherit its benefit through platform providers. By that time, quantum could very well be a one-line capability requirement simply required of platform vendors, just as we increasingly do today with AI. After all — past is prologue.
Andy LaMora is the Global Director of Data, Analytics and AI at Topcoder, the world’s largest technology talent network (1.5+M members in 190 countries) and digital crowdsourcing platform. Having spent more than a decade at Topcoder, LaMora is one of its most experienced leaders. He advises public and private organizations on the adoption of crowd strategies and use of data analytics to boost productivity and innovation.
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