Google Executive Says Quantum Applications Could Arrive in Five Years

Insider Brief

• A top Google executive told CNBC the company is about five years away from quantum computers running practical applications beyond classical capabilities.
• Google’s Julian Kelly said early uses may include simulating advanced physics problems and generating novel data, though AI-related uses remain speculative.
• Quantum interest is growing across the tech sector, with firms like Microsoft unveiling new chips and Nvidia hosting a summit despite concerns about long development timelines.
• Image: Google Quantum AI

One of Google’s top quantum computing executives says practical quantum applications are just five years away.

Julian Kelly, director of hardware at Google Quantum AI, told CNBC’s Deirdre Bosa that the company is approaching a milestone: a quantum computer capable of performing useful tasks that today’s most powerful machines cannot.

“We think we’re about five years out from a real breakout, kind of practical application that you can only solve on a quantum computer,” said Kelly in an interview aired yesterday.

His comments add to a growing debate about how quickly quantum computing will become more than a scientific curiosity. The field, long viewed as experimental, is now drawing fresh attention — and scrutiny — as big tech firms invest in developing machines that operate on the rules of quantum physics rather than conventional computing logic.

Quantum computers process information using qubits, short for “quantum bits.” Unlike traditional bits that are either a 0 or 1, qubits can seemingly exist in multiple probabilistic states, thanks to the principles of quantum mechanics. This gives them the potential to handle extremely complex problems, such as simulating chemical reactions or optimizing massive systems, tasks classical computers struggle to perform efficiently.

“Quantum computers speak quantum mechanics — they can access the way the universe works at the most fundamental level,” Kelly told CNBC.

Big Tech = Big Quantum

Google has previously demonstrated progress in quantum computing, including a 2019 claim of “quantum supremacy” — where a quantum machine completed a task faster than the best classical supercomputers. More recently, the company made headlines with an advance in quantum error correction, a critical step toward building reliable quantum systems. That advance was announced in December, as reported by CNBC.

Meanwhile, Microsoft has taken a different path. In February, the company introduced a quantum chip based on a particle called a Majorana, which it said required creating an “entirely new state of matter.” That work is still being challenged by the scientific community.

Still, even the most advanced machines remain far from the capabilities needed to deliver widespread practical value. Google’s current top system runs with 105 qubits. Experts estimate that a quantum computer will need over a million error-corrected qubits to tackle the kinds of problems that would have commercial or scientific value beyond what today’s supercomputers can do.

Near-Term Applications

Kelly acknowledged that gap, but said the earliest uses of quantum computing could arrive before reaching that scale. He pointed to potential near-term applications in simulating advanced physics.

“The first applications are likely to be in areas where you’ve got some system that’s sort of just out of reach of what a classical computer [can] do,” he said to CNBC.

One speculative application, Kelly said, involves using quantum machines to generate novel data that could help train artificial intelligence models. While he was cautious about overselling that idea, he said the intersection between AI and quantum computing is a subject of interest.

“One of the potential applications that you can think of for a quantum computer is generating new and novel data,” Kelly said.

However, he clarified that today’s AI systems won’t simply be ported to run on quantum computers, noting that the underlying models are fundamentally incompatible with the architecture of quantum machines.

Quantum computing’s perceived potential has helped propel investment, particularly as tech leaders and investors look for the next breakthrough in hardware after the boom in AI processors. Graphics processing units, or GPUs, made by Nvidia have powered the recent wave of AI development, and attention has begun to turn toward whether quantum chips could drive a similar revolution.

Though Nvidia doesn’t make quantum chips, it held a “Quantum Day” event last week. The summit featured representatives from Amazon, Microsoft, and a dozen quantum companies discussing the promise of the technology. According to CNBC, the event was seen by some as a signal that Nvidia is taking a more active role in the quantum space, even if only as an ecosystem enabler.

The meeting also followed public remarks by Nvidia CEO Jensen Huang, who in January had downplayed the near-term prospects of quantum computers. His comments, as reported by CNBC, triggered a dip in the share prices of several publicly traded quantum companies.

But last week, Huang softened his stance.

“Of course, quantum computing has the potential and all of our hopes that it will deliver extraordinary impact,” Huang said. “But the technology is insanely complicated.”

He added that his earlier comments were “wrong,” though he still maintained that many engineering hurdles remain before quantum computing becomes mainstream.

Timeline Divide

Industry observers remain divided on the timeline. Some see the recent advances by Google and Microsoft as signs that quantum computing is slowly but steadily progressing toward real-world utility. Others say predictions of a five-year breakthrough have been made before — and missed.

What is clear is that interest is rising. Venture capital investment in quantum startups is growing, and governments are increasing funding to compete in what many see as a strategic race. China, the U.S., and the European Union have all launched national quantum initiatives in recent years.

For now, companies like Google are focused on scaling up their machines and improving their reliability through better error correction and system integration. According to CNBC, Kelly remains confident that the hardware and software are evolving quickly enough to deliver something useful within the decade.

What that “something” is, and whether it’s truly beyond the reach of classical computers, remains to be seen.