Quantum computing is likely to become the next major technological advancement as the excitement around artificial intelligence diminishes. Amazon, Google, and Microsoft are at the forefront, continually working towards creating a reliable quantum bit, or qubit, the fundamental component of quantum computing.
All three companies have published research papers that detail the steps they’ve taken to make qubits a reliable data carrier. Their primary goal is to develop an error-correction technique that can be applied to the hundreds of thousands, or even millions, of qubits needed for 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.”
Amazon recently unveiled its quantum chip, dubbed Ocelot. Microsoft introduced its chip, Majorana 1, a week prior, and Google launched its processor, Willow, last December. All the chips are prototypes, and none of the error-correction techniques used completely solve the problem, according to West. However, they are incremental steps toward building enterprise-class quantum computing systems that may one day assist in drug discovery, provide a more complete understanding of climate change, and help in material creation 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.”
Analysts say that Microsoft is ahead of Amazon and Google in quantum advancement because the company has developed a unique state of matter to make qubits that carry data reliably. Amazon and Google use different approaches, but claim that they also have relatively high reliability rates. Amazon claims that its technique in Ocelot reduces errors by up to 90%.
The three companies are focused on developing quantum chips to avoid spending billions of dollars on the technology in the future, said David Nicholson, senior vice president and global technology advisor at The Futurum Group.
The launch of ChatGPT by OpenAI in late 2022 started the generative AI craze, which caused companies such as Amazon, Google, and Microsoft to pay Nvidia billions of dollars for the GPUs they need to train large-scale AI models in their clouds, including AWS, Google Cloud, and Azure. For the fiscal year ending January 26, Nvidia’s revenue exceeded $130 billion, with half of it coming from cloud providers.
“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.”
West said that within five years, the first quantum systems from cloud providers will be able to lower the cost and boost the performance of the enterprise services they offer today. Larger, more advanced quantum systems could be able to create new services in ten years. She believes that this timeline is short enough for businesses to begin planning for the quantum era now. They can consider how to acquire the skills that they will need to utilize this technology; this can be accomplished through internal training, hiring specialists, or using 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.
Today, organizations are talking to IDC and are not only looking at cloud providers for quantum computing, West said. Enterprises that want to know the complexities of the systems are using the cloud of quantum hardware vendors, including IBM and startups. Some startups in this field include QuEra Computing, Rigetti Computing, and SpinQ.
