Matthew Brisse is Research VP at Gartner.
Quantum computing technology is shrouded in myth and mystique – which is understandable when you consider the clichés bandied around when discussing it: “quantum computers will operate faster than the speed of light”. “Quantum computers will replace all conventional systems”.
“Quantum computing will render all security encryption algorithms obsolete”. CIOs have been inundated with hype, but must learn to cut through the noise to understand the disruptive power of quantum computing and its potential applications in artificial intelligence (AI), machine learning (ML) and data science.
While quantum solutions might well revolutionise the entire IT industry with considerable economic, industrial, and societal impacts, they won’t operate at light-speed, replace current systems, or render all security encryptions redundant overnight.
Quantum computing should not, however, be ignored. It holds enormous potential in areas of chemistry, optimisation, ML and AI, and will be able to address key opportunities in these areas which are currently inaccessible due to classic computer architecture limitations.
What is quantum computing?
Quantum computing is a type of non-classical computing based on the quantum state of subatomic particles. It differs fundamentally from classic computers, which operate using binary bits. Quantum computing uses quantum bits, or qubits. One qubit can represent a range of values, which is known as ‘superpositioning’.
Superpositioning grants quantum computers speed and parallelism, since each individual qubit can represent a quantitative solution to a problem. Qubits can also be linked together (known as “entanglement”). Each entangled qubit adds two additional dimensions to the system. Combined with superposition, quantum computers are capable of processing a massive number of possible outcomes at once. The number of high-quality qubits necessary to make a viable quantum computer depends on the problem.
The ability for a quantum computer to outperform a classical computer is called “quantum supremacy.” Experts forecast that quantum supremacy will become a reality within a matter of years for a limited number of computing problems.
Potential applications of quantum computing
Since general-purpose quantum computing is unlikely to ever make economic sense, applications for the technology will be narrow and highly focused. Nevertheless, the technology does hold the potential to revolutionise certain industries. Quantum computing could enable breakthroughs in:
- Machine learning: Improved ML through faster structured prediction. Examples include Boltzmann machines, quantum Boltzmann machines, semi-supervised learning, unsupervised learning and deep learning;
- Artificial intelligence: Faster calculations could improve perception, comprehension, and circuit fault diagnosis/binary classifiers;
- Chemistry: New fertilisers, catalysts, battery chemistries will all drive improvements in resource utilization;
- Biochemistry: New drugs, tailored drugs, and maybe even hair restorer;
- Finance: Quantum computing could enable faster, more complex Monte Carlo simulations; for example, trading, trajectory optimisation, market instability, price optimisation and hedging strategies;
- Healthcare: DNA gene sequencing, such as radiotherapy treatment optimisation/brain tumour detection, could be performed in seconds instead of hours or weeks;
- Materials: super strong materials; corrosion proof paints; lubricants and semiconductors;
- Computer science: Faster multidimensional search functions; for example, query optimisation, mathematics and simulations.
The risk of ignoring quantum computing
While many aspects of quantum computing’s future remain uncertain, such as the physics, materials, and controls, multinational organisations such as IBM, Google, Intel and Microsoft are already investing heavily in the hardware and software.
CIOs should consider quantum computing technology as a competitive advantage, as new quantum-inspired algorithms could produce innovative solutions and novel approaches to product development. It could also significantly reduce time to market, as well as optimising customer delivery.
Moreover, ignoring quantum computing may well place intellectual property (IP) and patent portfolios at risk: early adopters will enjoy a competitive advantage by patenting quantum-inspired innovations within specific domains. For example, a competitor might develop a quantum-based solution to improve Monte Carlo simulations by 1,000%, or a pharmaceutical company might significantly reduce the time to market for new drugs.
The realities of quantum computing
We are currently living through quantum winter – that is, the risk that hype outpaces development, potentially having a negative impact on perceptions and investments. Media hype is raising awareness while simultaneously setting unrealistic timeline and capability expectations. This level of hype is guaranteed to give way to disillusionment, which is particularly dangerous for quantum computing, as it requires sustained and focused investment for the long term.
As the fundamental physics of quantum computing remain in development, consistent results won’t appear for at least 5 to 10 years. Thus, any investments made in pursuit of quantum computing opportunities must pay off in monetisable discoveries.
The required logistics for quantum computers are specific: environments must be cooled to .015 Kelvin, and processors must be placed in dilution refrigerators shielded to 50,000 times less than the earth’s magnetic field. It also requires calibrating multiple times every day. These maintenance conditions are not viable for the majority of organisations. Gartner recommends that organisations interested in quantum computing leverage quantum computing as a service (QCaaS) to minimise risk and contain costs. By 2023, 95% of organisations researching quantum computing strategies will utilise QCaaS.
Overall, it remains safer to underinvest in the technology or to invest in skilled employees who can be fully productive as product managers in revenue-bearing areas. As quantum computing opportunities arise, these product managers will have the skills to address them. Gartner has identified surprising numbers of degreed quantum physicists in product management roles.
CIOs should focus on business value, and expect results to be at least 5 years out
By 2023, 90% of enterprise quantum computing investments will engage quantum consulting organisations to help shape problems that can leverage quantum algorithms. Knowing how to identify and extract business value from a quantum computing initiative is a key skill to develop. CIOs should look for potential opportunities from quantum computing and be ready to help the business leverage them.
These opportunities will need to be fully integrated with traditional IT, and will require new cross-collaboration from research scientists, computational data scientists and quantum data scientists. This new development paradigm is vital to the success of any quantum program.
Matthew Brisse is Research VP at Gartner.
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Matthew Brisse is Research VP for Gartner's Technical Professionals service focusing on data center modernization, migration and consolidation initiatives. Other topics include: quantum computing, colocation strategies, software-defined infrastructures, storage, disaster recovery and hybrid cloud architectures.