Amazon, Google, Microsoft race for first in quantum computing

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race for first in quantum computing

When the AI frenzy fades, quantum computing will likely become the next big thing in technology, with

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striving to stay at the forefront.

Each of the three companies has released research papers detailing the steps they’ve taken to make the fundamental unit of quantum computing, the qubit, a reliable data carrier. The companies are striving for an error-correction technique that would be workable across the hundreds of thousands to millions of qubits needed in a large-scale, practical quantum computer.

“Error correction is the puzzle piece that needs to be solved for these quantum systems to be able to scale and to be used to solve real-world problems,” said Heather West, research manager for quantum computing at IDC. “Until this is solved, these systems are only useful for small-scale experimentation.”

Last week,

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became the last of the three companies to unveil a quantum chip, which

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.

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introduced its chip,

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, the week before, and

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launched its processor,

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, last December. All the chips are prototypes.

None of the error-correction techniques used to develop the chips solve the problem completely, West said. Nevertheless, they are essential incremental steps toward building enterprise-class quantum computing systems that could one day assist in drug discovery, provide a more complete understanding of climate change, and help create materials for construction and manufacturing.

“I would keep it in perspective that this is still a marathon. It’s not a sprint,” West said. “There’s still a long way to go.”

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’s advancement is ahead of

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and

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because the company created a unique state of matter to make qubits that carry data reliably, analysts said.

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and

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used different techniques but also claimed relatively high reliability rates.

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claims its technique in Ocelot reduced errors by up to 90%.

The three companies are hell-bent on developing quantum chips to avoid having to shell out billions of dollars for the technology in the future, said David Nicholson, senior vice president and global technology adviser at The Futurum Group. The generative AI craze, which started with OpenAI’s release of ChatGPT in late 2022, forced

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and

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to pay Nvidia billions for the only GPUs available to train large-scale AI models in their respective clouds — AWS,

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Cloud and Azure.

For the fiscal year ending Jan. 26, Nvidia revenue was more than $130 billion, half of it from its cloud provider customers.

“These companies are saying they won’t be caught with their pants down [with quantum],” Nicholson said. “They’re not going to follow. They’re going to lead.”

In five years, the first quantum systems from cloud providers will lower the cost and increase the performance of the enterprise services they provide today, West said. Larger, more advanced quantum systems could make new services possible in 10 years.

The timeline is short enough for enterprises to start planning for the quantum era now, West said. They can consider where to get the skills necessary to take advantage of the technology, whether through in-house training, hiring specialists or leveraging third-party consulting agencies.

“That will take a little bit of time, so it’s definitely something to start planning toward, as well as trying to figure out what you want to do with [quantum],” West said. 

Organizations talking to IDC today are not looking at only cloud providers for quantum computing, West said. Enterprises that need to know the intricacies of the systems are using the cloud of quantum hardware vendors, including IBM and startups.

Startups in the space include QuEra Computing, Rigetti Computing and SpinQ.

Antone Gonsalves is an editor at large for Informa TechTarget, reporting on industry trends critical to enterprise tech buyers. He has worked in tech journalism for 25 years and is based in San Francisco. Have a news tip? Please drop him an email.

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#race #quantum #computing

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