When Lawrence Gasman was looking for a doctoral topic in the 1970s, computer labs were already full of smart people proposing smart studies in artificial intelligence. “But the problem was we didn’t have anything to operate them with,” he says. “The necessary processors simply didn’t exist.”
It took half a century for computing power to reach the potential of AI. Today, thanks to high-powered chips like GPUs from California-based Nvidia, generative artificial intelligence, or gen AI, is revolutionizing the way we work, study and consume entertainment, empowering people to create articles, images, videos and personalized videos. music in the blink of an eye. The technology has spawned a host of competing apps that offer improved speech recognition, graphic design, and even coding.
Now AI is poised to get another boost from a radical new form of computing: quantum. “Quantum could potentially do really remarkable things with AI,” says Gasman, founder of Inside Quantum Technology.
Instead of relying on the binary “bits” of traditional computing – switches denoted as 1s and 0s – quantum uses multivariant “qubits” that exist in some percentage of both states simultaneously, similar to a coin spinning in the air. The result is exponentially increased computing power, as well as an enhanced ability to intuitively mimic natural processes that rarely conform to a binary form.
While consumer-facing AI applications have made their impact more widespread and immediate, quantum is more industry-oriented, meaning that several recent milestones have flown under the radar. However, they can potentially supercharge 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 to advance generative AI. They are two perfect partners.”
Ultimately, AI depends on the ability to process huge piles of information, and that’s where quantum technology shines. In December, IBM unveiled its latest processor, dubbed heron, which has 133 qubits, the company’s best-ever error reduction and the ability to be interconnected in its first modular quantum computer, the System Two. Additionally, IBM revealed another chip, the Condor, which has 1,121 superconducting qubits arranged in a honeycomb pattern. These are advances that mean that “we are now 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.
Because qubits are incredibly delicate subatomic particles, they don’t always behave in the same way, which means quantum depends as much on increasing the total number of qubits to “verify” its calculations as it does on increasing the fidelity of each individual. Different technologies used to create a quantum effect prioritize different sides of this equation, making direct comparisons very complicated and highlighting the mysterious nature of the technology..
IBM uses superconducting qubits, which require cooling to near absolute zero to mitigate thermal noise, preserve quantum coherence, and minimize environmental interactions. However, Quantinuum uses alternative “trapped ion” technology that holds ions (charged atoms) in a vacuum using magnetic fields. This technology does not require refrigeration, although it is considered more difficult to scale. However, Quantanium claimed in April to have achieved 99.9% fidelity of its qubits.
“The trapped ion approach is way ahead of everyone else,” says Hazra. Gambetta, for his part, argues that quantum superconducting has advantages for scalability, speed of quantum interactions and leveraging existing semiconductor and microwave technology to make faster advances.
For impartial observers, the jury is still out, as the array of competing, non-linear metrics makes it impossible to say who is truly ahead in this race.. “These are very different approaches, both promising,” says Scott Likens, global leader of AI and innovation technology at business consultancy PwC. “We don’t see a clear winner yet, but it’s exciting.”
Gambetta and Hazra agree that quantum has the potential to combine with AI to produce truly impressive hybrid results. “I would love to see quantum technology for AI and AI for quantum technology,” says Gambetta. “The synergies between them and the advancement of technology in general make a lot of sense.”
Hazra agrees, saying that “generative AI needs the power of quantum computing to make fundamental advances.” For Hazra, the Fourth Industrial Revolution will be led by generative AI, but underpinned by the power of quantum computing. “The AI workload and the computational infrastructure of quantum computing are both necessary.”
It’s a vision shared across the Pacific, in China, where investments in quantum are estimated at around $25 billion, surpassing the rest of the world. China’s top quantum expert, Prof. Pan Jianwei, developed a Jiuzhang quantum computer that he says can perform certain types of AI-related calculations about 180 million times faster than the world’s largest supercomputer.
On a paper published in the peer-reviewed journal Physical Review Letters last May, Jiuzhang processed more than 2,000 samples from two common AI-related algorithms—Monte Carlo and simulated annealing—which would take the world’s fastest classical supercomputer five years, in less of one second. In October, Pan revealed Jiuzhang 3.0, which he claims is 10 quadrillion times faster at solving certain problems than a classic supercomputer.
Jiuzhang also uses a third form of quantum technology – light or photons – and Pan is widely praised as the king of quantum in China. A professor of physics at the University of Science and Technology of China, Pan in 2016 launched Micius, the world’s first quantum communications satellite, which transmitted entangled photons between Earth a year later for the world’s first quantum-safe video call.
Micius is considered quantum’s “Sputnik” moment, prompting American policymakers to funnel hundreds of millions of dollars into quantum information science through the National Quantum Initiative. Bills like the Innovation and Competition Act 2021 provided $1.5 billion for communications research, including quantum technology. The Biden administration’s proposal Budget for 2024 includes $25 billion for “emerging technologies,” including AI and quantum. Ultimately, quantum’s incredible computing power will soon make all existing cryptography obsolete, presenting a security migraine for governments and corporations around the world.
Quantum’s potential to turbocharge AI also applies to the latent technological competition between the world’s superpowers. In 2021, the US Department of Commerce added eight Chinese quantum computing organizations to its entity list, claiming they “support the military modernization of the People’s Liberation Army” and adopt American technologies to develop “anti-stealth and anti-submarine applications, and the ability to break encryption.”
These restrictions dovetail with a series of measures targeting China’s AI ambitions, including last year’s blocking Nvida to sell AI chips to Chinese companies. The question is whether competition between the world’s two leading economies impedes global progress in AI and quantum technology – or pushes individual nations to accelerate these technologies. The answer could have far-reaching consequences.
“AI can speed up quantum computing and quantum computing can speed up AI,” Google CEO Sundar Pichai counted the MIT Technology Review in 2019. “And collectively, I think it’s what we would need to, in the future, solve some of the most intractable problems we face, like climate change.”
Still, both the US and China have to overcome the same hurdle: talent. Although only a few universities around the world offer physics or quantum mechanics, courses dedicated to quantum computing are even rarer, and much less specialized knowledge in the various specialties. “Typically, the most valuable and scarce resource becomes the basis of your competitive advantage,” says Hazra. “And now, in the quantum area, it’s people with this knowledge.”
This story originally appeared on Time.com read the full story
