Quantum computing is having a moment. But the technology remains futuristic
Microsoft’s Majorana 1 quantum computing chip
Microsoft
It doesn’t quite have the buzz of artificial intelligence, but quantum computing is having a moment of its own.
Some of the most powerful institutions in the world, including Google, Microsoft, Amazon, IBM and the U.S. government, are spending many millions of dollars in a race to develop and build the first practical quantum computer.
Startups focused on quantum technology attracted about $2 billion last year, according to a McKinsey & Co. report, as investors pile into an industry that could have nearly $100 billion in revenue within a decade.
There isn’t much business today, though. In total, quantum computing companies generated under $750 million in revenue in 2024, according to the same report.
But more and more, we’re hearing about a big breakthrough.
In the past year, Microsoft unveiled its first quantum chip, Google executives said the technology may only be five years away, Amazon showcased its error-correcting quantum processor and IBM outlined its plan to build a meaningful quantum computer by 2029.
Joining them are scores of smaller companies and universities working on the underlying mathematics, software or potential business model. Some of the companies are even publicly traded, and can see their stocks soar or collapse based on a kernel of news.
In January, Nvidia CEO Jensen Huang sent quantum computing stocks reeling when he said 15 years was “on the early side” in considering how long it would be before quantum computing would be useful. He said at the time that 20 years was a time frame that “a whole bunch of us would believe.”
Two months later, he walked back the comments, but also expressed surprise that they moved markets, or that there were even markets to be moved.
“How could a quantum computer company be public?” Huang said in March.
Right now, there isn’t anything useful that quantum computers can do. They’re purely for research.
But the promise is clear. If the technology works, it can crunch certain kinds of numbers and do some tasks that are currently impossible on a traditional computer, or that would require so much time that the universe would end before they were completed.
To imagine a quantum computer, you have to fundamentally change how you consider what it means to compute.
A traditional computer works because there are billions of transistors on every chip. Those transistors can be ones or zeros — on or off. In large numbers, transistors can represent nearly every number, refer to parts of the system’s memory, and do arithmetic. That’s how every computer in the world works today.
In a quantum computer, the system uses qubits instead of transistors. It’s far more complicated than ones and zeros. Whether qubits are on or off is determined by quantum mechanics, and all of the qubits are “entangled,” which means a change in one will affect the probability of the others.
Making qubits work can require significant infrastructure. For example, some quantum computers have to be operated at very cold temperatures, near absolute zero.
So far, a lot of the applications for quantum have to do with simulating chemistry and physics.
“Quantum computers will not be the compute of choice for every application, and that’s OK,” said Krysta Svore, Microsoft’s vice president of advanced quantum development. “Even if we just use quantum computers for material science and chemistry, 96% of the world’s manufactured goods rely on chemistry and material science.”
Encryption
There’s one well-understood use for quantum computing today: encryption. That’s why the U.S. government and others around the world are closely tracking the technology’s development. It matters for national defense.
“The fear is that quantum computers will be able to crack our digital secrets,” said John Young, operating chief at the Americas division of Quantum eMotion, a quantum security company.
Currently, most passwords, WhatsApp texts, financial transactions and other important messages are encrypted, which means they’re scrambled and can’t be read if the data is stolen or observed. But quantum computers will be able to factor numbers quickly, which could allow hackers or other attackers to efficiently find the codes needed to decrypt important secrets.
Security researchers worry about what they call Q-Day, or the day when an effective quantum computer is created. They predict chaos when passwords and encryption start to mysteriously fail.
“Alongside its potential benefits, quantum computing also poses significant risks to the economic and national security of the United States,” the Biden White House said in 2022, in a national security memo. A cryptographically relevant quantum computer “could jeopardize civilian and military communications, undermine supervisory and control systems for critical infrastructure, and defeat security protocols for most Internet-based financial transactions,” the memo said.
There’s no practical application or algorithm that can be run on a quantum computer that can’t today be accomplished on a normal silicon-based, digital computer.
However, several groups say they’ve proven “quantum supremacy,” indicating that they’ve run a problem on a quantum computer that would’ve taken far longer with a traditional computer. The actions were all abstract.
Google was the first to declare quantum supremacy in 2019, describing its quantum computer’s accomplishment as a “benchmark.” The task it performed is called random circuit sampling, which is basically only used to test quantum computers.
Google says that researchers gave a computer random instructions to make a problem as complex under quantum mechanics as possible. Its researchers were then able to show that a quantum computer is faster at deciphering the quantum problem. Last year, Google said that its new, faster quantum computer Sycamore had expanded the performance gap.
In terms of future real-world applications, most of the potential for quantum computers is in the realms of medicine, chemistry and materials research.
Google points to drug discovery, or finding molecules that could be useful medicines. It also says that quantum computers will be able to do the science needed to commercialize fusion energy.
When Microsoft announced its first quantum chip in February, the company highlighted chemistry and materials science problems, like why some materials corrode, or how to compost plastic.
There is also some optimism that quantum computers will be well suited for generating training data for AI applications, especially for situations or problems with a huge number of potential solutions.
A general view of the Pentagon in Washington, D.C., U.S., March 21, 2025.
Kent Nishimura | Reuters
A Google researcher maintains a webpage that catalogs many of the most prominent quantum algorithms.
The most famous is Shor’s algorithm, which showed that a quantum computer would be able to find prime factors of a large number far faster than is currently possible on a digital computer.
When the algorithm was discovered in 1994, it ignited some concern from militaries around the world. Many of them use an encryption method called RSA, which needs the process of factoring large numbers to be difficult in order to keep data secret.
Worry about China
The fear is that a quantum computer would allow an adversary like China to quickly decode U.S. military messages or consumer banking transactions.
“Without effective mitigation, the impact of adversarial use of a quantum computer could be devastating to [national security systems] and our nation,” the Pentagon said in 2021.
Microsoft has acknowledged the national security factor, and has even framed quantum security as a race against China.
“While most believe that the United States still holds the lead position, we cannot afford to rule out the possibility of a strategic surprise or that China may already be at parity with the United States,” Microsoft President Brad Smith wrote in a blog post in April.
The government has led an effort to move encryption to so-called post-quantum methods, which can’t be broken by a quantum computer. Companies such as Apple have already started to integrate post-quantum encryption into its services like iMessage.
But past communications can still contain secrets. Intelligence agencies and other hackers often collect encrypted data in the expectation that one day it can be decrypted.
For now, much of the work in quantum is still fairly academic.
Most of the advanced hardware companies today are working on “error correction,” or a variety of methods meant to reduce the number of errors, and make them less harmful when they happen.
In present-day quantum computers, the qubits fail as often as 1 out of 1,000 times they are used, according to Microsoft researchers. Microsoft said last week that it was able to reduce the error rate by 1,000-fold thanks to a new approach.
Several improvements in error correction have been announced over the past year, which is one reason why researchers and engineers are increasingly confident that they’ll be able to build a quantum computer.
The next issue to address is scaling up the computers.
Google’s new Willow chip has 105 qubits. Microsoft’s Majorana chip has eight. IBM’s Starling plans to have 200 qubits. Amazon’s Ocelot chip has 14 qubits. In the coming years, these numbers have to go way up. Google and Microsoft say a truly useful quantum computer will need 1 million qubits.
Annealed neodymium iron boron magnets sit in a barrel at a Neo Material Technologies Inc. factory in Tianjin, China on June 11, 2010.
Bloomberg | Bloomberg | Getty Images
China’s exports of rare-earth magnets to the United States in June surged more than seven times from the prior month, as American firms clamor to get hold of the critical elements following a preliminary Sino-U.S. trade deal.
In April, Beijing placed restrictions on several critical magnets, used in advanced tech such as electric vehicles, wind turbines and MRI machines, requiring firms to receive licenses for export. The move was seen as retaliation against U.S. President Donald Trump’s steep tariffs on China.
Beijing has a stranglehold on the production of rare-earth magnets, with an estimated 90% of the market, as well as a similar hold on the refining of rare-earth elements, which are used to make magnets.
The U.S. received about 353 metric tons of rare-earth permanent magnets in June, up 660% from the previous month, data released by China’s General Administration of Customs showed, though the exports were about half that from June last year.
The U.S. was the second-largest destination for China’s rare-earth magnets, behind Germany, as it relies heavily on their imports for its large manufacturing sector, particularly automotive, electronics and renewable energy.
In total, China exported 3,188 metric tons of rare earth permanent magnets globally last month, up nearly 160% from May, but 38% lower compared with the same period last year.
The growth in exports came after Washington and Beijing agreed last month on a trade framework that included easing controls on Chinese rare-earth exports as well as a rollback of some American tech restrictions for shipments to China.
AI behemoth Nvidia said last week it was planning to resume shipments of its H20 AI chips to China, after the exports were restricted in April. Last month, controls on American AI chip software companies’ business in China had also been rolled back.
Chinese rare-earth magnet producers started announcing the approval of export licenses last month.
If exports continue to increase, it will be of great benefit to companies that have been suffering from shortages of magnets due to the lengthy time required to secure export licenses. For example, several European auto-parts suppliers were forced to halt production in recent months.
The magnet shortages had also hit emerging industries such as humanoid robotics. In April, Elon Musk said production of Tesla’s Optimus humanoid robots had been disrupted.
China’s controls on its rare-earths sector have prompted some global governments to reexamine their rare-earth supply chains and search for ways to support domestic mining of the minerals.
However, experts say that setting up alternatives to China’s rare-earth magnet supply chain could take years, as it requires an intricate process of rare-earth element refining and separation.
“The separation process is quite complex, and China has a lot of advantages in this after putting in decades of research into the processes,” Yue Wang, a senior consultant of rare earths at Wood Mackenzie, told CNBC last month.
One way that the U.S. has been trying to compensate for lack of rare-earth magnets is through increased recycling. Apple and miner MP Materials announced a $500 million deal last week for the development of a recycling facility that will reinforce the iPhone maker’s U.S. magnet supply chain.
Peter Alexander from financial consultancy Z-ben Advisors said that Washington’s latest concessions on tech restrictions were a reflection of just how much leverage China has in its trade relationship with the United States, speaking on CNBC’s “China Connection” on Monday.
The Huawei booth at the Mobile World Congress in Barcelona, 2025.
Arjun Kharpal | CNBC
Despite being beaten down by years of U.S. trade restrictions, China’s telecom giant Huawei has quietly emerged as one of the country’s fiercest competitors across the entire AI landscape.
Not only does the Shenzhen-based firm appear to represent Beijing’s answer to American AI chip darling Nvidia, but it has also been an early adopter of monetizing artificial intelligence models in industrial applications.
“Huawei has been forced to shift and expand its core business focus over the past decade… due to a variety of external pressures on the company,” said Paul Triolo, partner and senior vice president for China at advisory firm DGA-Albright Stonebridge Group.
This expansion has seen the company get involved in everything from smart cars and operating systems to the technologies needed for the AI boom, such as advanced semiconductors, data centers, chips and large language models.
“No other technology company has been able to be competent in so many different sectors with high levels of complexity and barriers to entry,” Triolo said.
This year, Nvidia CEO Jensen Huang has become increasingly vocal in calling Huawei “one of the most formidable technology companies in the world.” He has also warned that Huawei will replace Nvidia in China if Washington continues to restrict U.S. chip firms’ exports to the Asian country.
Nvidia surpassed $4 trillion in market capitalization last week to become the world’s most valuable company. Its cutting-edge processors and a related “CUDA” computing system remain the industry standard for training generative AI models and applications.
But that moat may be narrowing, as Huawei proves that it not only does it all, it does it well. While challenging American AI stalwarts like Nvidia is a tall order, the company’s history shows why it can’t be counted out.
Telephone switches to national champion
Huawei, which now employs more than 208,000 people across over 170 markets, came from humble beginnings. Founded by ambitious entrepreneur Ren Zhengfei in 1987 out of an apartment in Shenzhen, the firm started as a small telephone switch distributor.
As it grew into a telecoms player, it gained traction by targeting less developed markets such as Africa, the Middle East, Russia and South America, before eventually expanding to places like Europe.
By 2019, Huawei would be well-positioned to capitalize on the global 5G rollout, becoming a leader in the market. Around this time, it had also blossomed into one of the world’s largest smartphone manufacturers and was even designing smartphone chips through its chip design subsidiary, HiSilicon.
But Huawei’s success also attracted increasing scrutiny from governments outside China, particularly the U.S., which has frequently accused Huawei’s technology of posing a national security threat. The Chinese company has refuted such risks.
The export controls have ironically pushed Huawei into the arms of the Chinese government in a way that CEO Ren Zhengfei always resisted.
Paul Triolo
partner and senior vice president for China at DGA-Albright Stonebridge Group
Huawei’s business suffered a major setback in 2019 when it was placed on a U.S. trade blacklist, preventing American companies from doing business with it.
As the impact of the sanctions kicked in, Huawei’s consumer business – once the company’s largest by revenue – halved to about $34 billion in 2021 from the year before.
The company still managed a breakthrough on AI chips, and pressed ahead despite additional U.S. restrictions in 2020 that cut the company off from chipmaker Taiwan Semiconductor Manufacturing Co. A year earlier, Huawei officially launched its Ascend 910 AI processing chip as part of a strategy to build a “full-stack, all-scenario AI portfolio” and to become a provider of AI computing power.
But the U.S. targeting of Huawei also had the effect of turning the company into a martyr-like figure in China, building upon attention it received in 2018 when Meng Wanzhou, Huawei’s CFO and daughter of Ren, was arrested in Canada for alleged violations of Iran sanctions.
As the U.S.-China tech war continued to expand and broad advanced chip restrictions were placed on China, Huawei was an obvious choice to become a national champion in the race, with more impetus and state backing for its AI plans.
“The export controls have ironically pushed Huawei into the arms of the Chinese government in a way that CEO Ren Zhengfei always resisted,” Triolo said. In this way, the restrictions also became “the steroids” for Huawei’s AI hardware and software stack.
The comeback
After another year of declining sales in the consumer segment, the unit started to turn around in 2023 with the release of a smartphone that analysts said contained an advanced chip made in China.
The 5G chip came as a shock to many in the U.S., who didn’t expect Huawei to reach that level of advancement so quickly without TSMC. Instead, Huawei was reportedly working with Chinese chipmaker SMIC, a company that has also been blacklisted by the U.S.
While semiconductor analysts said the scale that Huawei and SMIC could produce these chips was severely limited, Huawei nonetheless had proved it was back in the advanced chip game.
It was also around this time that reports began surfacing about Huawei’s new AI processor chip, the Ascend 910B, with the company looking to seize upon gaps left by export controls on Nvidia’s most advanced chips. Mass production of the next-generation 910C is reportedly already on the way.
Subscribe now
To fill the void left by Nvidia, Huawei “has been making big strides in replicating the performance of high-end GPUs using combinations of lower chips,” said Jeffrey Towson, managing partner at TechMoat Consulting.
In April, Huawei unveiled its “AI CloudMatrix 384”, a system that links 384 Ascend 910C chips in a cluster within data centers. Analysts have said CloudMatrix is able to outperform Nvidia’s system, the GB200 NVL72, on some metrics.
Huawei isn’t just catching up, “it’s redefining how AI infrastructure works,” Forrester analysts said in a report last month about CloudMatrix.
Meanwhile, Huawei has also developed its own “CANN” software system that acts as an alternative to Nvidia’s CUDA.
“Winning the AI race isn’t just about faster chips. It also includes delivering the tools developers need to build and deploy large-scale models,” Forrester’s report said, though authors noted that Huawei’s products are still not integrated enough with other commonly used tools for developers to switch over quickly from Nvidia.
The ‘Ascend Ecosystem Strategy’
While Huawei’s goal to surpass Nvidia is seen as a key development in China and the U.S.’s race for AI, it’s important to note that chips represent just one building block of Huawei’s broader AI plans.
Huawei now has its hands throughout the artificial intelligence value chain, from chips to computing, to AI models and AI applications. These different AI business avenues also leverage other areas of the company’s vast technology empire.
In fact, the company’s “ICT Infrastructure” business — which includes 5.5G cellular network deployment and AI systems for industrial use — became the company’s largest revenue driver at 362 billion yuan in 2023.
The company has been deploying its Ascend AI chips and AI CloudMatrix 384 at its growing portfolio of AI data centers, which are operated by its cloud computing unit, Huawei Cloud, established in 2017 to compete with the likes of Amazon Web Services and Oracle.
These data centers, in turn, have provided the training capabilities and computing power used by Huawei’s suite of AI models under its Pangu series.
Unlike other general-purpose AI models like OpenAI’s GPT-4 or Google’s Gemini Ultra 1.0, Huawei’s Pangu model is designed to support more industry-specific applications across the medical, finance, government, industrial and automotive sectors. Pangu has already been applied in more than 20 industries over the last year, the company said last month.
Rolling out such AI applications often involves having Huawei tech staff working for months at the project site, even if it’s in a remote coal mine, Jack Chen, vice president of the marketing department for Huawei’s oil, gas and mining business unit, which provides digital and intelligent solutions to transform these industries, told CNBC.
That research enabled the company in May to deploy more 100 electric-powered trucks that can autonomously transport dirt or coal using the telecom company’s 5G network, AI and cloud computing services.
And it’s not limited to China. The technology can “be replicated on a large scale in Central Asia, Latin America, Africa, and the Asia-Pacific,” Chen said.
Huawei has also open-sourced the Pangu models, in a move it said would help it expand overseas and further its “Ascend ecosystem strategy,” which refers to its AI products built around its Ascend chips.
Speaking to CNBC’s “Squawk Box Asia” on Thursday, Patrick Moorhead of Moor Insights & Strategy said he expected Huawei to push Ascend in countries part of China’s Belt and Road Initiative — an investment and development project aimed at emerging markets.
Over a period of five to 10 years, the company could begin to build serious market share in these countries, in the same way it once did with its telecommunications business, he added.
-
Sports3 years ago‘Storybook stuff’: Inside the night Bryce Harper sent the Phillies to the World Series
-
Sports1 year agoStory injured on diving stop, exits Red Sox game
-
Sports2 years agoGame 1 of WS least-watched in recorded history
-
Sports2 years agoMLB Rank 2023: Ranking baseball’s top 100 players
-
Sports4 years ago
Team Europe easily wins 4th straight Laver Cup
-
Sports2 years agoButton battles heat exhaustion in NASCAR debut
-
Environment2 years agoJapan and South Korea have a lot at stake in a free and open South China Sea
-
Environment2 years agoGame-changing Lectric XPedition launched as affordable electric cargo bike