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Quantum computing has the potential to greatly accelerate breakthroughs in everything from pharmaceuticals to predicting stock market behavior — and these advances could be right around the corner, according to IBM (IBM-2.53%) CEO Arvind Krishna.
Artificial intelligence is all the rage in the tech industry, but the current generation of AI won’t get the industry to an all knowing artificial general intelligence model, Krishna said on Tuesday at SXSW in Austin, Texas. Breakthroughs are instead expected to come from AI working in complement with quantum computing.
“AI is learning from already produced knowledge, literature, graphics and so on, it is not trying to figure out what is going to come,” Krishna said.
Quantum computers instead work on the subatomic level and are probabilistic models. Quantum computing technology, when achieved in full, has the potential to be much faster than regular computers and could go beyond what AI systems can provide to give insights into “how nature behaves,” the IBM chief said, particularly on a sub-atomic level.
“Once we know how nature behaves, then we can learn a lot more, because none of that is in existing knowledge,” Krishna said.
The industry’s belief in how fast quantum computing technology can scale up has wavered recently. Earlier this year, Nvidia CEO Jensen Huang and Meta chief Mark Zuckerberg claimed that useful quantum computers are 15-30 years away, which tanked quantum computing stocks like IonQ (IONQ+1.92%) and Rigetti Computing (RGTI+0.63%).
Although the technology has more progress it needs to count, Krishna believes that quantum computing is “going to surprise you before this decade is up.”
He isn’t the only person to believe this either. Microsoft (MSFT+0.60%) co-founder Bill Gates told Yahoo Finance last month that quantum computing could become useful in as soon as 3 to 5 years.
And there have been recent advancements in quantum computing, most notably in December when Google (GOOGL-0.62%) unveiled its latest quantum chip Willow. Google claims the chip will greatly reduce error rates, one of the greatest challenges plaguing quantum technology.
On the other hand, the biggest problems facing AI, according to Krishna, are a lack of domain specificity — in depth knowledge of particular fields or application areas — as well as the technology’s notorious energy intensity.
“I’ll predict for you that five years from now, most of the models are going to be using 1% of the energy of what they’re using today,” Krishna said. “I think DeepSeek gave us a preview.”
Quantum computing, while still costly, has the potential to be less energy intensive than AI data centers.
Krishna also said that IBM is working on building practical use cases for the technology, not just investing in making the quantum computing hardware.
“In the end, to me, value in technology is not derived from the invention. Much as we love the invention, value is derived from people using it,” Krishna said.
“Sometimes, when we get ahead of ourselves, we get too focused on the invention and not on making sure that there are hundreds and thousands of different companies, private and public, that are using it. So that’s what we’re trying to get done in this case and I think we’re kind of going at the right pace in this instance,” he added.
Industry leaders will be getting together on March 20th for Nvidia’s (NVDA+3.21%) first “Quantum Day,” at the tech giant’s GPU Technology Conference to discuss where quantum computing is headed.
