It makes sense that sci-fi-level myths might surround a technology that must be stored in a container colder than interstellar space and has the potential to solve some of the world’s most challenging problems.
CIOs have been inundated with quantum computing hype: “Quantum computers will operate faster than the speed of light,” or “Quantum computers will replace conventional systems” or “Quantum computing will render all security encryption algorithms obsolete.”
Quantum solutions could revolutionize the entire IT industry
The truth is that quantum solutions could revolutionize the entire IT industry with major economic, industrial, academic and societal impacts. But they won’t operate faster than light travels or replace current computing systems, and although they’ll challenge some security encryptions, they won’t render them all obsolete overnight.
“Quantum computing is heavily hyped and evolving at different rates, but it should not be ignored,” says Matthew Brisse, VP Analyst, Gartner. “It holds great promise, especially in the areas of chemistry, optimization, machine learning and AI to name a few. Today’s data scientists simply cannot address key opportunities in these areas because of the compute limitations of classic computer architectures.
“Some of these problems may take today’s fastest supercomputers months, or even years, to run through a series of permutations, making it impractical to attempt,” says Brisse. “Quantum computers have the potential to run complex calculations that classical systems could literally never complete. This potential for compute acceleration, as well as the ability to address difficult and complex problems, is what is driving so much interest from CEOs in a variety of industries.”
What is quantum computing?
Quantum computing is a type of nonclassical computing based on the quantum state of subatomic particles. Quantum computing is fundamentally different from classic computers, which operate using binary bits. This means the bits are either 0 or 1, true or false, positive or negative. However, in quantum computing, the bit is referred to as a quantum bit, or qubit. Unlike the strictly binary bits of classic computing, qubits can, strangely, represent a range of values in one qubit. This representation is called “superpositioning.”
Superpositioning is what gives quantum computers speed and parallelism, as each qubit can represent a quantitative solution to a problem. Further, qubits can be linked with other qubits in a process called entanglement; each entangled qubit adds two more dimensions to the system. When combined with superposition, quantum computers can process a massive number of possible outcomes at the same time.
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.” While it may sound like a sci-fi dream, experts believe that for a limited number of computing problems, quantum supremacy will be a reality in a matter of years.
Potential applications of quantum computing
Applications for quantum computing will be narrow and focused, as general-purpose quantum computing will most likely never be economical. However, the technology does hold the potential to revolutionize certain industries. Quantum computing could enable breakthroughs by:
- Machine learning: Improved ML through faster structured prediction. Examples include Boltzmann machines, quantum Boltzmann machines, semisupervised learning, unsupervised learning and deep learning.
- Artificial intelligence: Faster calculations could improve perception, comprehension, and circuit fault diagnosis/binary classifiers.
- Chemistry: New fertilizers, 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 optimization, market instability, price optimization and hedging strategies.
- Healthcare: DNA gene sequencing, such as radiotherapy treatment optimization/brain tumor detection, could be performed in seconds instead of hours or weeks.
- Materials: super strong materials; corrosion proof paints; lubricants; semiconductors
- Computer science: Faster multidimensional search functions; for example, query optimization, mathematics and simulations.
Is encryption at risk?
Researchers have shown how quantum computing could kill, or at least significantly weaken, current cryptography systems. If true, this would jeopardize any business that relies on encryption. If a sufficiently powerful quantum computer becomes available within 10 or so years, any data that has been published or intercepted is subject to cryptanalysis by a future quantum computer.
Most security professionals speculate that quantum computing will eventually render RSA cryptography and ECC useless but will not be able to effectively counter hash, code, lattice-based or multivariate-quadratic-equations cryptography. Symmetric key cryptographic systems like Advanced Encryption Standard (AES), SNOW 3G, 3GPP and Kerberos are resistant to a quantum computing attack if they use a large-enough key size. The problem is, researchers keep coming up with new key cracking algorithms. For this reason, governments are investing in a cousin to quantum computing — quantum key distribution.
The risk of ignoring quantum computing
The physics, materials and control systems of quantum computers remain uncertain, but the potential for disruption is driving large organizations like IBM, Google, Intel and Microsoft to heavily invest in quantum hardware and software. Startups in multiple industries are emerging, alongside new skill sets — from quantum algorithm experts and designers to quantum circuit engineers and applied physicists.
CIOs should view quantum computing as a competitive advantage, as new quantum-inspired algorithms could bring innovative solutions and approaches to product development. It could also reduce time to market and optimize customer delivery.
Additionally, waiting or ignoring quantum computing might place intellectual property (IP) and patent portfolios at risk. Early organizations will have the competitive advantage by patenting quantum inspired innovations within their specific domains. For example, a rival company could develop a quantum inspired innovation that improves Monte Carlo simulations by 1,000% or a pharmaceutical company could shorten the time to market for new drugs.
The realities of quantum computing
As with any new technological innovation, there is a risk that the hype outpaces product development, which could negatively impact perceptions and investments. In the case of quantum computing, this is called quantum winter. Hype in the media is creating awareness and advancement, but also setting unrealistic expectations for timing and capabilities. This level of hype inevitably leads to disillusionment, which is dangerous, as quantum computing requires sustained, focused investment for the long term.
The hype around quantum computing makes it interesting as an investment. However, the fundamental physics are still in development, and consistent results won’t appear for at least 5 to 10 years — and possibly much longer. Therefore, any investments made in pursuit of quantum computing opportunities must pay off in monetizable discoveries.
By 2023, 95% of organizations researching quantum computing strategies will utilize QCaaS
Logistically, quantum computers are difficult to maintain and require specialized environments cooled to .015 Kelvin. The quantum processor must be placed in a dilution refrigerator shielded to 50,000 times less than the earth’s magnetic field and placed in a high vacuum to 10 billion times lower than atmospheric pressure. It will also need calibration several times per day. For most organizations, this is not feasible. Gartner recommends that organizations interested in quantum computing leverage quantum computing as a service (QCaaS) to minimize risk and contain costs. By 2023, 95% of organizations researching quantum computing strategies will utilize QCaaS.
Overall, it remains safer to underinvest in the technology or to invest in skilled personnel 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 found 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
Gartner projections should be used to manage expectations inside the organization. Take this time to identify opportunities to provide support to clients or customers, or leverage industry breakthroughs. Consider looking to the R&D group for support and ensure you have access to a resource who can help you translate quantum technology into opportunities in your business.
By 2023, 90% of enterprise quantum computing investments will engage quantum consulting organizations 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. IBM, Microsoft and others have customer engagement services for organizations interested in identifying potential business opportunities that quantum computing could someday address.
What to do next?
Gartner predicts that by 2023, 20% of organizations will be budgeting for quantum computing projects, compared to less than 1% today. CIOs should look for potential opportunities from quantum computing and be ready to help the business leverage them.
By 2023, 20% of organizations will be budgeting for quantum computing projects
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 critical to the success of any quantum program.
It is time to learn more about quantum computing.
This article has been updated from the original, published on November 29, 2017, to reflect new events, conditions or research.