What's the current state of quantum computing?
As quantum computing comes closer to being a reality, learn how this style of computing can coexist with traditional computing. Discover major players and key use cases.
Many large tech companies have already invested heavily in quantum technologies, yet significant adoption of quantum computing has had its share of delays and false starts. However, with some recent announcements in the quantum sector, now seems to be the ideal time for organizations to take a closer look at quantum and consider how this approach could work for their business workloads. Organizations that have been historically focused on classical computing are now positioning quantum for the future.
In an ESG IT spending survey, 11% of respondents indicated their organizations were piloting quantum for a few applications, 17% indicated they are testing and 24% of respondents have begun research but are years away from production apps. Finally, 27% have expressed an interest in quantum computing but have not taken any action toward embracing it.
This slow growth in adoption is about to change -- and possibly quickly. As leading organizations explore new ways to produce faster results, accelerate buying cycles and improve performance, they have become more open to shifting away from purely classical solutions to accelerate adoption of quantum.
The dynamic shift and market alignment
The industry is also discovering new methods and use cases that can be applied from classical to quantum computing platforms. Take, for example, the recent merger between Quantum Computing Inc. (QCI) and QPhoton, a quantum photonics company. Bill McGann, COO and CTO at QCI, discussed the merger.
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Based on the information he shared, it seems that the combination of QCI and QPhoton capabilities can deliver a quantum computer that makes quantum systems more accessible for organizations, so they can see business results faster and more cost effectively. Another benefit of this merger is that the companies are broadening the user base to non-quantum experts, many of whom have been anxiously awaiting the opportunity to explore quantum-possible problems in areas like analytical optimization and drug discovery.
Using a full-stack approach, QCI and QPhoton together offer a unique opportunity to accelerate the delivery of practical quantum applications. This is the same process that drove value in classical computing. The merger of the two companies extends the QCI portfolio to help accelerate the accessibility of quantum computing for today's use cases, such as AI and optimization. This also enables quantum computing to operate at room temperatures, which is often a challenge with this type of computing.
Classical vs Quantum use cases
When it comes to the finance use case, one way to understand how to pivot from classical to quantum computing is to think through how algorithms work.
For example, take a traditional investor model. With a financial algorithm, you must understand and look at predefined user parameters, such as investment goals, risk tolerances and diversity of funds. In this scenario, the investor wants to understand the user's investment preferences and risk tolerances. This data is "parameterized" -- meaning variables are created and passed on to the quantum computing model, which could use an artificial intelligence model employed by the quantum-compliant Monte Carlo algorithm or other techniques to process the investor's instructions, analyze the global asset-universe stochastic data and produce corresponding investor-inquiry output results.
Another emerging focus or concept coming out of the investor model is enabling users to autonomously process and analyze stochastic financial asset data. An interface -- proprietary or not -- could enable users to provide predefined input parameters representing their investment preferences and risk-tolerance levels, and then produce independent customized solutions for each user.
Depending on the type of user inquiry or request for analysis, a version of AI -- such as autonomous dispersion analytics or autonomous diversification and allocation machine learning -- could deploy to process the instructions and analyze asset stochastic data. This process would be very difficult to achieve in classical computing environments.
Quantum: On the horizon
As IBM chief quantum exponent Robert Sutor explained in a blog post from last July, "Quantum computers will solve some problems that are completely impractical for classical computers." This indicates that organizations plan to adopt quantum into their existing environments.
"[QCI is committed to be the] democratizing force that empowers non-quantum experts to realize quantum value," said Robert Liscouski, CEO of QCI. The recent acquisition of QPhoton accelerates this ease-of-use approach.
Here are some thoughts to consider:
- There are hardware approaches -- IBM and Honeywell, for example -- and software approaches -- e.g., Google, AWS -- to quantum computing.
- Vendors have been working with some of their specific centers of excellence and doing extensive investigation out of the CTO office.
- Top vendors leading this initiative are IBM, QCI, Xanadu, Microsoft Azure Quantum and D-Wave Systems.
Although it is still early days for quantum computing, vendors in this area -- such as HPE, Dell and IBM -- are seeing some interesting use cases, and they are exploring them with partners and customers. If they can couple quantum computers with HPC systems, hey believe quantum computers can accelerate certain workloads. In this model, quantum computing can become an accelerator attached to a standard HPC system.
So, who in corporate IT is buying quantum solutions? According to quantum companies, data scientists in education, scientist labs and researchers are the primary users, while common buyers include airline businesses, financial institutions and academia. The conversations focus on the top five applications for initial quantum, which include but are not limited to the following targeted sectors: optimization, research, crypto, finance, materials science and healthcare.
Making moves in the market
Microsoft is making headway with Azure Quantum without a huge investment of hardware. These emulators also have a consortium of companies backing them. QCI, Honeywell, Toshiba, IonQ and iCloud are vendors that discussed their approach, using Azure to achieve their goals.
Google Quantum AI is mostly based on a simulator, but its progress has slowed down since its initial launch in 2019. The Sycamore computer shows potential but is still in its early stage. Amazon Web Services has a quantum computing center focused on R&D, testing and operating quantum processors to innovate and scale tech to support new, large-scale initiatives.
Quantum defines its growth by three horizons:
- Horizon 1, also called now or near term, includes transactional use cases such as credit scoring, vehicle routing, chemical design, chemistry and drug/protein structure prediction.
- Horizon 2, also called near term, follows with oil processing and shipping, refining processes, drilling, livestock, disruption management and supply chain issues, investment risk analysis, clinical trial acceleration, optimization of manufacturing and fabrication.
- Horizon 3, also called future looking, consists of seismic imaging, consumer recommendation with financial analysis, disease risk prediction and structural design for buildings.
Why does any of this matter?
The promise of the quantum computer has been coming for a long time -- and the concept is now becoming a reality. The use of scaling of qubits in real-world environments is showing real potential.
According to Investopedia, "Quantum computing is an area of computing focused on developing computer technology based on the principles of quantum theory (which explains the behavior of energy and material on the atomic and subatomic levels)." When we look at today's computers, they are designed to encode information in bits that use values of 1 or 0, therefore restricting their ability to achieve this next level of processing. Quantum is a completely new way of computing that differs significantly from what we do today on traditional classical systems.
There are many companies trying to get in front of this "wave" because quantum processing is incredibly fast. Solving today's problems would be completed in a fraction of time. However, not all use cases work with quantum. The traditional systems coexist with quantum systems now and will continue to do so in the future.
ESG is a division of TechTarget.