MIT researchers, in collaboration with Accenture, have developed a framework to help businesses understand the potential of quantum computing. Quantum computers can solve complex problems faster than classical computers, with applications in areas such as simulating matter behavior, creating new drugs, and identifying fraud in financial transactions. However, the technology is not expected to be ready for complex problems until 2035 or later. The researchers suggest that quantum computing will be most beneficial for large problems with exponential algorithmic gains and processing large datasets. Key researchers involved include Neil Thompson, Sukwoong Choi, and William S. Moses.
“This framework provides a way to analyze the potential impact of switching to quantum computing before making the investment,”
Neil Thompson.
Understanding Quantum Computing and Its Business Implications
Quantum computing, a technology that applies the principles of quantum mechanics to solve complex problems, is predicted to have a significant impact on businesses. This technology can solve large-scale problems much faster than classical computers. Examples include simulating the behavior of matter, analyzing compounds to create new drugs, optimizing factory floors or global supply chains, and identifying fraud and risk patterns in financial transactions.
However, the current field of quantum computers is not yet ready for widespread use. McKinsey estimates that 5,000 quantum computers will be operational by 2030, but the hardware and software necessary for handling the most complex problems won’t be available until 2035 or later. Despite this, organizations need to start considering how they might leverage this technology to solve real-world business problems. Some companies already expect to invest more than $15 million annually in quantum computing.
MIT Researchers Develop Framework for Quantum Computing Evaluation
A team of researchers from MIT, in collaboration with Accenture, has developed a framework to help tech-savvy executives evaluate the potential of quantum computing for problem-solving in their companies. The team includes Neil Thompson, a research scientist at MIT Sloan and the MIT Computer Science and Artificial Intelligence Laboratory, Sukwoong Choi, an assistant professor at the University of Albany and a digital fellow at the MIT Initiative on the Digital Economy, and William S. Moses, an assistant professor at University of Illinois Urbana-Champaign.
The framework provides a way to analyze the potential impact of switching to quantum computing before making the investment. The researchers concluded that small to moderate-sized problems, the most common types for typical businesses, will not benefit from quantum computing. However, those trying to solve large problems with exponential algorithmic gains and those that need to process very large datasets will derive advantages.
An Overview of Quantum Computing
Quantum computing was first proposed in the 1980s and involves using quantum bits (qubits), which are subatomic particles, to represent combinations of both ones and zeros simultaneously. The more qubits, the greater potential for large-scale compute power for problem-solving. This concept was further developed by MIT mathematician Peter Shor, who developed the first well-known quantum algorithm for breaking encryption in the 1990s.
When Quantum Computing Will Be Useful
The researchers’ framework aims to help businesses determine whether the shorter route or the faster computer is more valuable, depending on what problem they are trying to solve. Scientists are striving to achieve quantum advantage, which is the ability to use quantum computers to solve problems that are beyond the reach of classical computers. Some companies are estimated to reach the quantum advantage by 2030.
The researchers also introduced the concept of quantum economic advantage, which occurs when a particular problem can be solved more quickly with a quantum computer than with a comparably priced classical computer. To determine the quantum economic advantage, business and technology leaders will have to consider two conditions: feasibility and algorithmic advantage.
Current State and Future of Quantum Computing
Quantum computing is early in the maturity cycle, but the landscape is heating up. IBM launched Osprey, a 433-qubit machine, last year and has set its sights on building a 100,000-qubit machine within 10 years. Google is targeting a million qubits by the end of the decade. Other players in the nascent space include D-Wave Systems, IonQ, Rigetti Computing, Honeywell, Microsoft, Intel, and PsiQuantum. Fortune Business Insights has projected that the quantum computing market will grow from $928.8 million this year to $6.5 billion by 2030.
However, challenges remain in the development, cost, and talent acquisition of quantum computing. Companies are still figuring out how to scale the number of physical qubits that can be built into quantum computing systems, as well as optimizing how the different qubits interact with one another. The technology is also expensive, given that the systems require intricate cooling technologies to shield the qubits. The skills gap is another problem, with McKinsey predicting that by 2025, fewer than half of quantum jobs will be filled.
“Implicitly, there’s a race going on between the classical computer and quantum computer. For each type of question you want to solve, you want to know which type of computer will win so you can take the best advantage of it,” – Neil Thompson, a research scientist at MIT Sloan and the MIT Computer Science and Artificial Intelligence Laboratory.
“Quantum computing is not going to be better for everything, just for some things,” – Neil Thompson.
“Think of it like a race in getting from point A to point B, and the algorithm is the route,” Thompson said. “If the race is short, it might not be worth investing in better route planning. For it to be worth it, it has to be a longer race.” – Neil Thompson.
Summary
Quantum computing, which applies the laws of quantum mechanics to solve complex problems, could have a significant impact on businesses, potentially solving large-scale problems faster than classical computers. However, a framework developed by MIT researchers suggests that while quantum computing may benefit those dealing with large problems and large datasets, it may not offer advantages for small to moderate-sized problems typically encountered by businesses.
- Quantum computing, which applies the laws of quantum mechanics to solve complex problems, could have a significant impact on businesses.
- MIT researchers, in collaboration with Accenture, have developed a framework to help businesses evaluate the potential of quantum computing for problem-solving.
- The researchers, including Neil Thompson from MIT and Sukwoong Choi from the University of Albany, suggest that quantum computing will be beneficial for solving large problems with exponential algorithmic gains and processing very large datasets.
- Quantum computers use quantum bits (qubits), which can represent combinations of ones and zeros simultaneously, increasing their potential for large-scale problem-solving.
- The researchers’ framework helps businesses determine whether a shorter route or a faster computer is more valuable, depending on the problem they are trying to solve.
- The concept of quantum economic advantage is introduced, which occurs when a problem can be solved more quickly with a quantum computer than with a comparably priced classical computer.
- Major players in the quantum computing field include IBM, Google, D-Wave Systems, IonQ, Rigetti Computing, Honeywell, Microsoft, Intel, and PsiQuantum.
- Challenges in the field include scaling the number of physical qubits, decreasing error rates, high costs, and a skills gap.
- Quantum computing is expected to be useful sooner for small-scale problems and later for solving more complex problems.
