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Quantum Matters: Quantum & AI – Early Days For a Killer Combination

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Guest Post by Karina Robinson

Artificial Intelligence (AI) suffers from two massive blocks: colossal, costly energy use and a transparency deficit. The technology can be technically feasible but is still too expensive for most organisations to consider it. That was the conclusion of a recent paper from MIT Future Tech, which looked at computer vision tasks as an example of an AI-enabled technology. But the MIT group isn’t alone in highlighting the problem.

The computing cost of Deep Learning is exploding. Sam Altman, CEO of OpenAI, made it clear last year that training ever larger Language Learning Models (LLM) is not the way to advance AI, not least because teaching GPT-4, its latest product, cost over $100m, while by 2027 it is estimated that the AI industry could consume as much power as a country the size of the Netherlands.

On the openness front, the models are far too opaque – usable in consumer applications but a legal minefield for companies to consider rolling out. Their tendency to ‘invent’ plausible facts is also not helpful.

Quantum is the route through which AI’s limitations can be lifted.

Two perception issues are delaying the advance. Firstly, there is an impediment to AI/Quantum cooperation based on misapprehensions that quantum is only about hardware – creating a quantum computer with enough power to break current encryption. That is unlikely to happen for several years. It may take up acres of media space, but much more advanced are quantum sensors, some of which are already in the market, while in quantum communication the Chinese are apparently more advanced, and quantum software/quantum-inspired software is advancing at pace. All of these are based on quantum physics and applicable to AI in different ways.

The second issue is the silo mentality of many of the companies involved in these fields, who have separate divisions for AI and Quantum, or only concentrate on one. Nevertheless, more visionary firms are breaking through the barrier.

Scott Faris, CEO of US firm Infleqtion says, “The convergence of AI and Quantum is one of the most powerful combinations that we are starting to unlock. The convergence will have both immediate and long-term implications.”

Karina Robinson is Senior Advisor to Multiverse Computing and Founder of The City Quantum & AI Summit

The firm, which manufactures quantum products and parts, ranging from sensors to computer hardware, counts NASA as one of its clients. Faris points out that quantum-enabled technologies are “quickly demonstrating their utility in addressing the crushing data infrastructure scaling challenges driven by AI. Scaled networks of quantum sensors will create vast new data sets of unparalleled precision and value which will be unlocked by parallel advancements in AI.”

A case in point is CompactifAI, the product launched late last year by Multiverse Computing*. Europe’s largest quantum software and quantum-inspired software firm, which counts Bosch and the Bank of Canada among its clients, uses its technology to compress the data from a Large Language Model (LLM) by up to 70%, thus using much less computing power, and achieve results that are comparable in quality.

“Left on its own, AI is going to burn the world by consuming intolerable levels of energy,” says CEO Enrique Lizaso. His firm, shortlisted as one of three finalists in the European Future Unicorn Award, is using its AI and quantum-inspired capabilities in fields ranging from forecasting weather catastrophes – on the increase with global warming – to helping car manufacturers in the training of their Machine Vision.

This is done on the premises of the industrial site, rather than data processing centres, with faster retraining of the multiple streams of data, reduced processing power requirements and added security.

Lizaso is adamant that the cross over between AI and Quantum is environmentally helpful in other ways. He notes that optimising routes for shipping, for instance, or optimising the amount of fuel tankers need for a journey, cuts back on the carbon footprint of the ship.

Nvidia, best known as the AI chip market leader, is also keen on quantum.

“AI is accelerating quantum computing today. We’re starting to see researchers tap into the mature infrastructure of AI and accelerated computing to leverage things like Large Language Models (LLMs) to develop new quantum algorithms and improve the performance of quantum computers,” says Tim Costa, who leads the HPC and Quantum Computing Product Team.

“We are just starting to scratch the surface of how Gen AI can improve quantum computing,” he adds, noting however, that in the near term researchers are already investigating quantum machine learning (QML) and quantum-inspired methods for financial applications like fraud detection and forecasting.

Recently, researchers from the University of Toronto, St. Jude Children’s Research Hospital and NVIDIA developed a new quantum algorithm called the “GPT-Quantum Eigensolver.” It uses the framework of generative AI models to generate quantum circuits with desirable properties, in this case to calculate the ground state energy of molecules of interest. Versions of this generative quantum algorithm can be applied towards important problems in drug and new materials discovery, as well as a host of other applications, some of which we cannot even imagine.

As for the problem with the unclear thinking process of AI, and its fantasising, quantum is also part of the answer.  To use it more widely, the interpretability of the system is key – in essence understanding why a system makes the decisions it does so it can be held accountable. Only last week Quantinuum, formed from the merger of Cambridge Quantum and Honeywell Quantum, announced a first public step in creating AI that is “interpretable and accountable” via the development of a framework for compositional models of AI using a type of maths called category theory. Their academic paper has yet to be peer reviewed.

Humankind’s biggest challenges will not be solved tomorrow by the combination of Quantum & AI. Nevertheless, at the risk of creating a hostage to fortune, I would predict many will be solved in the next decades by those firms at the forefront of the Quantum & AI journey.

*Karina Robinson is Senior Advisor to Multiverse Computing and Founder of The City Quantum & AI Summit which takes place on Monday, October 7th.

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When: July 13, 2023 at 11:30am

What: GenMat Webinar

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The Quantum Insider is the leading online resource dedicated exclusively to Quantum Computing. You can contact us at [email protected].

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The Future of Materials Discovery: Reducing R&D Costs significantly with GenMat’s AI and Machine Learning Tools

When: July 13, 2023 at 11:30am

What: GenMat Webinar

Jake Vikoren

Jake Vikoren

Company Speaker

Deep Prasad

Deep Prasad

Company Speaker

Araceli Venegas

Araceli Venegas

Company Speaker

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