Quantum is the next step toward the future of analytics and computing. Is your organization ready for it?
Quantum computing can solve challenges that modern computers can't--or it might take them a billion years to do so. It can crack any encryption and make your data completely safe. Google reports that it has seen a quantum computer that performed at least 100 million times faster than any classical computer in its lab.
Quantum blows away the processing of data and algorithms on conventional computers because of its ability to operate on electrical circuits that can be in more than one state at once. A quantum computer operates on Qubits (quantum bits) instead of on the standard bits that are used in conventional computing.
Quantum results can quickly make an impact on life science and pharmaceutical companies, for financial institutions evaluating portfolio risks, and for other organizations that want to expedite time-to-results for processing that on conventional computing platforms would take days to complete.
Who is using quantum computing?
Few corporate CEOs are comfortable trying to explain to their boards what quantum computing is and why it is important to invest in it.
"There are three major areas where we see immediate corporate engagement with quantum computing," said Christopher Savoie, CEO and co-founder of Zapata Quantum Computing Software Company, a quantum computing solutions provider backed by Honeywell. "These areas are machine learning, optimization problems, and molecular simulation."
Savoie said quantum computing can bring better results in machine learning than conventional computing because of its speed. This rapid processing of data enables a machine learning application to consume large amounts of multi-dimensional data that can generate more sophisticated models of a particular problem or phenomenon under study.
Quantum computing is also well suited for solving problems in optimization. "The mathematics of optimization in supply and distribution chains is highly complex," Savoie said. "You can optimize five nodes of a supply chain with conventional computing, but what about 15 nodes with over 87 million different routes? Add to this the optimization of work processes and people, and you have a very complex problem that can be overwhelming for a conventional computing approach."
A third application area is molecular simulation in chemistry and pharmaceuticals, which can be quite complex.
In each of these cases, models of circumstances, events, and problems can be rapidly developed and evaluated from a variety of dimensions that collate data from many diverse sources into a model.
"The current COVID-19 crisis is a prime example," Savoie said. "Bill Gates knew in 2015 that handling such a pandemic would present enormous challenges—but until recently, we didn't have the models to understand the complexities of those challenges."
Quantum computing is still very new
For those engaging in quantum computing and analytics today, the relative newness of the technology presents its own share of glitches. This makes it important to have quantum computing experts on board. For this reason, most early adopter companies elect to go to the cloud for their quantum computing, partnering with a vendor that has the specialized expertise needed to run and maintain quantum analytics.
"To do quantum computing tasks at any meaningful scale, these companies will generally need to leverage modern scalable and portable multi-cloud deployment architectures such as Kubernetes clusters," Savoie said. "They code a quantum circuit that contains information on how operations are to be performed on quantum qubits. From there, the circuit and the prepared data are sent to the cloud, which performs the quantum operations on the data. The data is processed in the cloud and sent back to the on-prem stack, and the process repeats itself until processing is complete."
Savoie estimated that broad adoption of quantum computing for analytics will occur within a three- to five-year timeframe, with early innovators in sectors like oil and gas, and chemistry, that already understand the value of the technology and are adopting sooner.
"Whether or not you adopt quantum analytics now, you should minimally have it on your IT roadmap," Savoie said. "Quantum computing is a bit like the COVID-19 crisis. At first, there were only two deaths; then two weeks later, there were ten thousand. Quantum computing and analytics is a highly disruptive technology that can exponentially advance some companies over others."
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