Quantum Computing and AI: A Perfect Match?

What happens when you link together the two leading disruptive IT technologies? A new field with almost unlimited research and development potential.

John Edwards, Technology Journalist & Author

June 14, 2024

5 Min Read
Futuristic microchip processor with lights blue AI background.
tcharts via Alamy Stock Photo

It's a marriage that could only happen in cyberspace -- quantum computing and artificial intelligence. 

Quantum AI is a burgeoning computer science sector, dedicated to exploring the potential synergy that exists between quantum computing and AI, says Gushu Li, a professor at the University of Pennsylvania School of Engineering and Applied Science, in an email interview. "It seeks to apply principles from quantum mechanics to enhance AI algorithms." A growing number of researchers now believe that AI models developed with quantum computing will soon outpace classical computing AI development. 

Quantum AI creates an intersection between quantum computing and artificial intelligence, observes Román Orús, chief scientific officer at quantum computing software development firm Multiverse Computing, via email. He notes that quantum computing has the potential to take AI to entirely new levels of performance. "For instance, it's possible to develop quantum neural networks that teach a quantum computer to detect anomalies, do image recognition, and other tasks." Orús adds that it's also possible to improve traditional AI methods by using quantum-inspired approaches to dramatically reduce the development and training costs of large language models (LLMs). 

Related:Demystifying Quantum Computing: Separating Fact from Fiction

Potential Applications 

Combining the quantum physics properties of superposition and entanglement, which can perform limitless processes simultaneously with machine learning and AI, and suddenly it's possible to do more than ever imagined, says Tom Patterson, emerging technology security lead at business advisory firm Accenture, via email. "Unfortunately, that includes being used by adversaries to crack our encryption and develop new and insidious ways to separate us from our information, valuables, and anything else we hold dear." 

Still, Patterson is generally optimistic. Like ChatGPT, he expects quantum AI to arrive gradually, and then all at once. "While full use of an AI-relevant quantum computer remains years away, the benefits of thinking about AI with quantum information science capabilities are exciting and important today," he states. "The opportunities are here and now, and the future is brighter than ever with quantum AI." 

For his part, Li believes that quantum AI's biggest initial impact will be in four specific areas: 

  • Drug Discovery: Simulating molecules to design new drugs and materials with superior properties. 

  • Financial Modeling: Optimizing complex financial portfolios and uncovering hidden trends in the market. 

Related:Cybersecurity's Future: Facing Post-Quantum Cryptography Peril

  • Materials Science: Developing new materials with specific properties for applications like superconductors or ultra-efficient solar cells. 

  • Logistics and Optimization: Finding the most efficient routes for transportation and optimizing complex supply chains. 

A Silent Revolution 

Quantum AI is already here, but it's a silent revolution, Orús says. "The first applications of quantum AI are finding commercial value, such as those related to LLMs, as well as in image recognition and prediction systems," he states. More quantum AI applications will become available as quantum computers grow more powerful. "It's expected that in two-to-three years there will be a broad range of industrial applications of quantum AI." 

Yet the road ahead may be rocky, Li warns. "It's well known that quantum hardware suffers from noise that can destroy computation," he says. "Quantum error correction promises a potential solution, but that technology isn't yet available." 

Meanwhile, while quantum AI algorithms are being developed, classical computing competitors are achieving new AI successes. "While progress is being made, it's prudent to acknowledge that the integration of quantum computing with AI is a complex endeavor that will unfold gradually," Li says. 

Related:What Is the Future of AI-Driven Employee Monitoring?

Patterson notes that many of the most promising quantum AI breakthroughs aren't arriving from university and corporate research teams, but from various regional developer and support communities that closely mirror natural ecosystems. "Regions that have decided that quantum and AI are too big and too important to leave to one group or another have organized around providing everything progress demands -- from investment to science to academics to entrepreneurs, growth engines, and tier-one buyers," he says. "These regional ecosystems are where the magic happens with quantum AI." 

Mind-blowing 

GenAI and quantum computing are mind-blowing advances in computing technology, says Guy Harrison, enterprise architect at cybersecurity technology company OneSpan, in a recent email interview. "AI is a sophisticated software layer that emulates the very capabilities of human intelligence, while quantum computing is assembling the very building blocks of the universe to create a computing substrate," he explains. "We're pushing computing both into the realm of the mind and the realm of the sub-atomic." 

The transition to quantum AI won't be optional, Orús warns, since current AI is fundamentally flawed due to excessive energy costs. New models and methods will be needed to lower energy demands and to make AI feasible in the long term. "Early adopters of quantum AI will get a competitive advantage and will survive, as opposed to those that do not adopt or adopt it too late." 

About the Author(s)

John Edwards

Technology Journalist & Author

John Edwards is a veteran business technology journalist. His work has appeared in The New York Times, The Washington Post, and numerous business and technology publications, including Computerworld, CFO Magazine, IBM Data Management Magazine, RFID Journal, and Electronic Design. He has also written columns for The Economist's Business Intelligence Unit and PricewaterhouseCoopers' Communications Direct. John has authored several books on business technology topics. His work began appearing online as early as 1983. Throughout the 1980s and 90s, he wrote daily news and feature articles for both the CompuServe and Prodigy online services. His "Behind the Screens" commentaries made him the world's first known professional blogger.

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