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KWhen Lawrence Gasman was looking for a PhD topic in the 1970s, computer labs were already teeming with smart people proposing clever work on artificial intelligence. “But the problem was, we had nothing to run them on,” he says. “The processors needed were not available.”
It has taken half a century for computing power to reach the potential of artificial intelligence. Today, California-based Nvidia’s GPUs are revolutionizing the way we work, study, and consume entertainment, enabling people to create custom articles, images, videos, and content, thanks to high-powered chips like generative AI, or gene AI. Music in the blink of an eye. The technology has spawned a multitude of competing consumer apps that offer advanced voice recognition, graphic design, and even coding.
Now artificial intelligence is ready to get a new boost from quantum, a radical new form of computing. “Quantum can potentially do some really remarkable things with AI,” says Gasman, founder of Inside Quantum Technology.
Rather than relying on the binary “bits” (keys represented as 1s and 0s) of traditional computing, quantum uses multivariate “qubits” that exist in a percentage of both states simultaneously, similar to a coin spinning through the air. The result is exponentially increasing computing power as well as an increased ability to intuitively mimic natural processes that rarely obey binary form.
While consumer-targeted applications of AI genes are making their impact more widespread and rapid, quantum is more industry-oriented, meaning some recent milestones have been overlooked. But they will potentially accelerate the AI revolution.
“Generative AI is one of the best things to happen to quantum computing,” says Raj Hazra, CEO of Colorado-based quantum start-up Quantinuum. “And quantum computing is one of the best things that can happen in the advancement of generative AI. “They are two excellent partners.”
After all, AI relies on its quantum-superior ability to process huge chunks of information. In December, IBM introduced its newest processor, called Heron, which has 133 qubits, boasts the firm’s best-ever error reduction and the ability to interconnect with System Two, the first modular quantum computer. In addition, IBM also introduced Condor, another chip containing 1,121 superconducting qubits arranged in a honeycomb pattern. “These are advances that mean we’re now getting into something I call ‘quantum utility,’ where quantum is used as a tool,” Jay Gambetta, vice president of IBM Quantum, tells TIME.
Because qubits are incredibly delicate subatomic particles, they don’t always behave the same way; This means that quantum relies on both increasing the overall number of qubits to “control” their calculations and increasing the fidelity of each individual. The different technologies used to create the quantum effect prioritize different sides of this equation, making direct comparisons very difficult and reinforcing the secretive nature of the technology..
IBM uses superconducting qubits that require cooling to near absolute zero to reduce thermal noise, maintain quantum coherence, and minimize environmental interactions. But Quantinuum uses alternative “forbidden ion” technology, which traps ions (charged atoms) in a vacuum using magnetic fields. Although this technology does not require cooling, it is considered more difficult to scale. However, Quantanium claimed in April that its qubits had achieved 99.9% fidelity.
“The trapped ion approach is miles ahead of everyone else,” says Hazra. Gambetta, however, argues that quantum superconducting has advantages in terms of scale, speed of quantum interactions, and leveraging existing semiconductor and microwave technology to make advances faster.
For impartial observers, the jury is still out because a plethora of competing, non-linear metrics make it impossible to tell who is ahead in this race.. “These are very different approaches, and both show promise,” says Scott Likens, global AI and innovation technology leader at business consultancy PwC. “We still don’t see a clear winner, but it’s exciting.”
What Gambetta and Hazra agree on is that quantum combined with artificial intelligence has the potential to produce truly spectacular hybrid results. “I would love to see quantum for AI and AI for quantum,” says Gambetta. “The synergy between them and the advancement in technology in general makes a lot of sense.”
Hazra agrees and says that “generative AI needs the power of quantum computing to make fundamental advances.” According to Hazra, the Fourth Industrial Revolution will be led by productive artificial intelligence but supported by the power of quantum computing. “The workload of artificial intelligence and the computing infrastructure of quantum computing are both required.”
This is a view shared across the Pacific in China, where quantum investments are estimated to be around $25 billion, dwarfing the rest of the world. China’s best quantum expert Prof. Pan Jianwei has developed a Jiuzhang quantum computer that he claims can perform certain types of artificial intelligence-related calculations approximately 180 million times faster than the world’s best supercomputer.
In a paper published last May in the peer-reviewed journal Physical Review Letters, Jiuzhang analyzed more than 2,000 examples of two common AI-related algorithms—Monte Carlo and simulated annealing—that would take the world’s fastest classical supercomputer five years in less than a second. it worked. . In October, Pan introduced Jiuzhang 3.0, which it claims is 10 quadrillion times faster than a classical supercomputer at solving certain problems.
Jiuzhang uses a third form of quantum technology (light or photons), and Pan is widely praised as China’s quantum king. Pan, a physics professor at the University of Science and Technology of China, launched Micius, the world’s first quantum communications satellite, in 2016 and a year later beamed entangled photons between Earth for the world’s first quantum-secured video call.
Micius is considered quantum’s “Sputnik” moment, prompting American policymakers to pour hundreds of millions of dollars into quantum information science through the National Quantum Initiative. Bills like the Innovation and Competitiveness Act of 2021 provided $1.5 billion for communications research, including quantum technology. The Biden Administration’s proposed 2024 budget includes $25 billion for “emerging technologies,” including artificial intelligence and quantum. After all, the awesome computing power of quantum will soon make all existing cryptography obsolete, creating a security migraine for governments and companies around the world.
Quantum’s potential to turbocharge AI also applies to the ever-increasing technology competition between the world’s superpowers. In 2021, the US Department of Commerce added eight Chinese quantum computing 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 applications and capabilities.” To break the encryption.”
These restrictions dovetail with a series of measures targeting China’s AI ambitions, including last year blocking Nvidia from selling AI chips to Chinese firms. The question is whether the competition between the world’s two largest economies is holding back overall progress in AI and quantum, or pushing each country 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 MIT Technology Review in 2019. “And collectively, I think that’s ultimately what we need to solve some of the most challenging problems we face, like climate change.”
Yet both the US and China need to overcome the same hurdle: talent. While only a few universities worldwide offer quantum physics or mechanics, specialized courses in quantum computing, let alone specialization in various specializations, are even rarer. “Often the most valuable and scarce resource becomes the foundation of your competitive advantage,” says Hazra. “And there are people in quantum right now who have this knowledge.”
Write to: Charlie Campbell at charlie.campbell@time.com.