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WHen Lawrence Gasman was looking for PhD material back in the 1970s, computer labs were already buzzing with smart people proposing smart studies of artificial intelligence. “But the problem was we didn’t have anything to run them,” he says. “The required processors were not there.”
It took half a century for computing power to catch up with the capabilities of AI. Today, thanks to high-powered chips such as GPUs from California-based Nvidia, next generation artificial intelligence, or gen AI, is revolutionizing the way we work, study and consume entertainment. , which enables people to create articles, images, videos and custom videos. music in the blink of an eye. Plenty of competing consumer apps have emerged from the technology that offer improved voice recognition, graphic design, and even coding.
Now AI is poised to get another boost from a radical new type of computing: quantum. “Quantum could do some amazing things with AI,” says Gasman, founder of Inside Quantum Technology.
Rather than relying on the binary “bits” of traditional computing—switches denoted as 1s and 0s—quantum multivariate “qubits” exist in some percentage of both states at the same time, like a coin spinning in the middle . The result is exponentially boosted computing power as well as an enhanced ability to intuitively mimic natural processes that rarely adhere to binary form.
While gen AI’s consumer-focused applications have a more widespread and immediate impact, quantum is more industry-focused, meaning some recent milestones have fallen under the radar. However, they could turbocharge the AI revolution.
“Generative AI is one of the best things to happen to quantum computing,” says Raj Hazra, CEO of Colorado-based quantum startup Quantinuum. “And quantum computing is one of the best things to happen in terms of advancing generational AI. They are two perfect partners.”
Ultimately, AI relies on the ability to crunch massive stacks of information, which is where quantum excels. In December, IBM unveiled its latest processor, called Heron, which has 133 qubits, the firm’s best-ever error reduction and the ability to be linked together within its first modular quantum computer, System Two . In addition, IBM unveiled another chip, Condor, which has 1,121 superconducting qubits arranged in a honeycomb pattern. They are a breakthrough that means “now we’re entering what I like to call ‘quantum utility,’ where quantum is being used as a tool,” Jay Gambetta, vice president of IBM Quantum, tells TIME.
Since qubits are extremely sensitive subatomic particles, they do not always behave in the same way, which means that quantum relies on increasing the total number of qubits to “check” their calculations as well as boost everyone’s loyalty. Different technologies used to create a quantum effect prioritize different aspects of this equation, making direct comparisons very difficult and adding to the technology’s idiosyncratic nature..
IBM uses superconductor qubits, which require cooling to near absolute zero to mitigate thermal noise, preserve quantum consistency, and minimize environmental interactions. However, Quantinuum uses another “trapped ion” technology that holds ions (charged atoms) in a vacuum using magnetic fields. This technology does not require cooling, although it is thought to be more difficult to scale. However, Quantanium claimed in April that it had achieved 99.9% fidelity of its qubits.
“The trapped ion approach is miles ahead of everyone else,” says Hazra. Gambetta, in turn, argues that quantum superconducting has advantages in terms of scaling, the speed of quantum interactions, and leveraging existing semiconductor and microwave technology to make progress faster.
For unbiased observers, the jury is still out as the many competing, non-linear metrics make it impossible to say who is ahead in this race.. “They are very different approaches, and both are promising,” says Scott Likens, global AI and technology innovation leader for business consultancy PwC. “We don’t see a clear winner yet, but it’s exciting.”
Where Gambetta and Hazra agree is that quantum meshing with AI has the potential to produce truly terrifying hybrid results. “I would love to see quantum for AI and AI for quantum,” says Gambetta. “The synergies between them, and the advancements in technology in general, make a lot of sense.”
Hazra agrees, saying that “generative AI needs the power of quantum computing to make fundamental progress.” In Hazra’s case, the Fourth Industrial Revolution will be led by generational AI but underpinned by the power of quantum computing. “Both AI workload and quantum computing computing infrastructure are essential.”
It’s a view shared across the Pacific in China, where quantum investments are estimated to be around $25 billion, leaving the rest of the world behind. China’s top quantum expert Professor Pan Jianwei has developed the Jiuzhang quantum computer, which he claims can perform certain types of AI-related calculations about 180 million times faster than the world’s best supercomputer.
In a paper published in the peer-reviewed journal Physical Review Letters last May, Jiuzhang processed more than 2,000 examples of two popular AI algorithms – Monte Carlo and simulated annealing – that would take five years on the world’s fastest classical supercomputer, in one second. . In October, Pan revealed Jiuzhang 3.0, which he claims was 10 quadrillion times faster in solving certain problems than a classic supercomputer.
Jiuzhang still uses a third type of quantum technology – light or photons – and Pan is widely hailed as China’s quantum king. A physics professor at the University of Science and Technology of China, Pan in 2016 launched Micius, the world’s first quantum communication satellite, which took off with photons employed between the earth a year later for the world’s first quantum-sponsored video call.
Micius is seen as a quantum “Sputnik” moment, prompting American policymakers to funnel hundreds of millions of dollars into quantum information science through the National Quantum Initiative. Bills such as the Innovation and Competitiveness Act of 2021 have provided $1.5 billion for communications research, including quantum technology. The Biden Administration’s proposed 2024 budget includes $25 billion for “emerging technologies” to includes AI and quantum. Ultimately, the awesome computing power of quantum computing will soon render all existing cryptography obsolete, presenting a security migraine to governments and corporations everywhere.
Quantum’s potential to turbocharge AI is also about the simmering technological competition between the world’s superpowers. In 2021, the US Department of Commerce added eight Chinese quantum computer organizations to its Entity List, claiming that they support the military modernization of the People’s Liberation Army and adopt American technologies to “develop anti-stealth and anti-submarine warfare applications , and the ability. to break encryption.”
These restrictions combine with a series of measures aimed at China’s AI ambitions, including last year blocking Nvidia from selling AI chips to Chinese firms. The question is whether competition between the world’s top two economies hinders overall AI and quantum progress — or whether it pushes each nation to accelerate these technologies. The answer could have far-reaching consequences.
“AI can accelerate quantum computing, and quantum computing can accelerate AI,” Google CEO Sundar Pichai told the MIT Technology Review in 2019. “And collectively, I think what We would, quite rightly, need to solve some of the more difficult ones. problems we face, such as climate change.”
However, the US and China have to overcome the same obstacle: talent. Although only a handful of universities around the world offer quantum physics or quantum mechanics, dedicated courses on quantum computing, let alone expertise in the various specialties within, are rare. “Typically, your most valuable and scarce resource will form the basis of your competitive advantage,” says Hazra. “And now in quantum it is people who have that knowledge.”
Write to Charlie Campbell at charlie.campbell@time.com.
