• Google unveiled its Willow chip this week, marking a milestone in the quantum computing space.
• One quantum researcher compared Google's advancement to mobile networks jumping from 1G to 2G.
• While the news represents a breakthrough, real-world applications are likely still years away.

Google's new Willow chip may not show up in consumer products in the near future — however, quantum computing researchers say it represents a significant breakthrough in the field.

That's because the chip solves a challenge that's existed in quantum computing for nearly 30 years, Google said in its announcement earlier this week.

The challenge is reducing the amount of errors quantum computers generate while operating. Quantum computers aren't your standard laptop or desktop computer.

Unlike your laptop, which uses bits to process information, quantum computers use something called qubits, short for quantum bits. Bits are binary digits, meaning they can only exist in one state at a time, typically as a 0 or 1. Qubits, on the other hand, can exist in multiple states simultaneously.

That's important because it means you can process significantly more information at much faster speeds with qubits. That's the ultimate promise of quantum computers: They can process so much data in such short periods that they'll revolutionize science and medicine, helping us solve problems related to climate change and health, for example, that are far too complex to tackle with today's technology.

However, right now, the best quantum computers can perform around a thousand operations before errors overwhelm the processing system, Steve Brierley, quantum computing researcher and CEO of error correction company Riverlane, told Business Insider.

"If we want to get to this big potential like transformational technology, we need to get to millions and trillions of free operations," Brierley said.

That's where Google's Willow chip has made a significant breakthrough. With the Willow chip, the more qubits Google adds, the fewer errors the system creates. The Willow chip reduces errors exponentially, the company said. The ability to reduce errors while scaling qubits is known in the field as being "below threshold," and it's been an unresolved challenge since 1995.

This plays out via processing speed. Google said its researchers used the Random Circuit Sampling benchmark to compare computing speeds across various technologies. The RCS is a standard in the field and the "classically hardest" benchmark to pass, to compare computing speeds across various technologies.

Google said its Willow chip can perform the standard benchmark computation in under five minutes, which would take one of the fastest supercomputers 10 septillion years to complete — longer than the known age of the universe.

In the field of quantum, error correction is much more difficult and requires more hardware to function properly, which is why Google's advancement is so important, Mark Saffman, professor at the University of Wisconsin-Madison and director at the Wisconsin Quantum Institute, told BI.

Brierley compared Google's quantum computing advancement to what mobile networks experienced when they shifted from 1G to 2G networks.

When mobile networks shifted from 1G to 2G, "Qualcomm added error correction into the stack and this created a huge uplift in capability," Brierley said. "And this is exactly what's happening right now in quantum computing."

The ability to constantly correct errors is a "key part" of building a quantum computer, he said. Once companies are able to scale qubits and advance quantum computing forward, they will be able to reach the point of real-world applications.

Real-world impact is likely years away

Google said in a press briefing about the development that it has already partnered with companies in the pharmaceutical, material science, and battery space, among others. However, advancements in those fields may not be right around the corner.

Saffman said he would like to see real-world applications in five years, but it's difficult to provide an exact number.

Sebastian Weidt, quantum computer professor at the University of Sussex and co-founder and CEO of quantum computing company Universal Quantum, told BI that "we're still a little while away" from quantum computing impacting the general public.

Weidt said that while there was initially hope that intermediate-scale computers could offer some value to a general consumer, the science shows that qubits need to be scaled by hundreds of thousands and eventually millions to unlock real-world applications.

"There are many major roadblocks on their roadmap that need to be overcome for that technology to get to that scale," Weidt said.

Still, Google's advancement moves quantum computing research to the next stage — and while investors may not be able to reap the benefits in the immediate short term, Brierley said announcements like this help attract capital and talent to the space.

"There's still very very far to go to make it useful relative to conventional computers," Saffman said. "But it's a great step forward."

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• Elon Musk's demand for Nvidia chips has put pressure on the company to deliver.
• A Nvidia sales lead told colleagues in an email that their supply chain was under strain, per the Journal.
• A Nvidia spokesperson told BI that the company has "worked hard to meet the needs of all customers."

Nvidia is feeling the pressure from trying to meet Elon Musk's insatiable demand for chips.

Musk's demand for chips was straining the chip giant's supply chain, a sales lead for Nvidia told colleagues in an email obtained by The Wall Street Journal.

The Journal's report, which was published on Wednesday, did not specify when the email was sent.

When approached for comment, a spokesperson for Nvidia told Business Insider that the company has "worked hard to meet the needs of all customers."

Nvidia has also "greatly expanded the available supply" of its chips, the spokesperson added.

Musk did not respond to a request for comment from BI.

Nvidia's chips have become a hot commodity among tech companies, who use them to train and deploy their AI models.

In January, Meta CEO Mark Zuckerberg told The Verge in an interview that Meta would own more than 340,000 Nvidia H100 GPUs by the end of 2024.

"We have built up the capacity to do this at a scale that may be larger than any other individual company. I think a lot of people may not appreciate that," Zuckerberg told the outlet.

Musk, meanwhile, has been building his own war chest of chips. The billionaire launched his own AI startup, xAI, in 2023 and has since raised billions of dollars in funding.

In June, CNBC reported that Musk had redirected $500 million worth of Nvidia chips from Tesla to X and xAI.

"Tesla had no place to send the Nvidia chips to turn them on, so they would have just sat in a warehouse," Musk said on X in response to CNBC's story.

Then, in September, Musk announced that xAI had brought a massive new training cluster of Nvidia chips online.

The system, dubbed Colossus, was built using 100,000 Nvidia H100 GPUs in Memphis, Tennessee, in 122 days, Musk wrote on X.

"Colossus is the most powerful AI training system in the world. Moreover, it will double in size to 200k (50k H200s) in a few months," Musk said in his post.

The engineering feat was praised by Nvidia's founder and CEO, Jensen Huang, who called it a "superhuman" feat.

"As far as I know, there's only one person in the world who could do that. Elon is singular in his understanding of engineering and construction and large systems and marshaling resources," Huang said in an interview on the "Bg2 Pod" podcast that aired on October 13.

"It's just unbelievable," Huang added.

Musk and Zuckerberg aren't the only tech executives hungry for Nvidia's chips.

Larry Ellison, the cofounder and chairman of Oracle, said in an earnings call in September that he and Musk had asked Huang for more GPUs while the three were having dinner.

"I would describe the dinner as me and Elon begging Jensen for GPUs," Ellison said.

The robust demand for chips has turned Nvidia into one of the most valuable companies in the world.

Nvidia announced its third-quarter earnings on November 20, where it recorded $35.08 billion in revenue for the quarter — a 94% year-over-year increase. The company's shares are up by 173% year to date.