A woman bikes by a giant Google logo at Google’s Bay View campus in Mountain View, California on Aug 13, 2024 where the “Made by Google” media event was held today.
Josh Edelson | AFP | Getty Images
Google has unveiled a new chip that it says marks a major breakthrough in the field of quantum computing, an area seen as the next frontier for many tech companies.
However, while Google’s achievements have been noted for advancing the field, experts say that quantum computing still has no real-world uses — yet.
“We need a ChatGPT moment for quantum,” Francesco Ricciuti, associate at venture capital firm Runa Capital, told CNBC Tuesday, referencing OpenAI’s chatbot that has been credited with driving the boom in artificial intelligence. “This is probably not that.”
What has Google claimed?
Proponents of quantum computing claim it will be able to solve problems that current computers can’t.
In classical computing, information is stored in bits. Each bit is either a one or zero. Quantum computing uses quantum bits or qubits which can be zero, one or something in between.
The theory is that quantum computers will be able to process much larger volumes of data, leading to potential breakthroughs in areas like medicine, science and finance.
“Typically the more qubits you use, the more errors will occur, and the system becomes classical,” Hartmut Neven, founder of Google Quantum AI, wrote in a blog post.
Willow can reduce errors “exponentially” as the number of qubits is scaled up, the U.S. tech giant said, which “cracks a key challenge in quantum error correction that the field has pursued for almost 30 years.”
Google measured Willow’s performance using the so-called random circuit sampling (RCS) benchmark, which presents a computational task that’s difficult for classical computers to solve.
Willow performed a computation in under five minutes that would take one of today’s fastest supercomputers 10 septillion years — or 10,000,000,000,000,000,000,000,000 years — Google said.
“This mind-boggling number exceeds known timescales in physics and vastly exceeds the age of the universe,” Neven said.
Has Google truly made a quantum breakthrough?
Google’s Willow chip has demonstrated a “new milestone in how quantum computers can deal with errors that happen during their operation,” according to Winfried Hensinger, professor of quantum technologies at the University of Sussex.
“Their technique becomes more effective in reducing errors the more extra qubits are being used to correct for these errors. This is a very important milestone for quantum computers.”
But despite optimism that quantum computing could one day change the world — or at least computers’ role in it — experts in the field have suggested that Google’s quantum computing breakthrough is still lacking in real-world uses.
Runa Capital’s Ricciuti said that Google’s claims of success are “based on tasks and benchmarks that are not really useful for practical cases.”
“They are trying to define a really high problem for normal computers that they can solve with quantum computers. It is amazing they can do that, but it doesn’t really mean it is useful,” Ricciuti added.
Hensinger said Willow “is still well too small to do useful calculations” and that quantum computers will require “millions of qubits” to solve really important industry problems. Willow has 105 qubits.
Meanwhile, Google’s chip is based on superconducting qubits, a technology that requires intense cooling, which could be a limiting factor in scaling up.
“It may be fundamentally hard to build quantum computers with such large number of qubits using superconducting qubits as cooling so many qubits to the required temperature – close to absolute zero – would be hard or impossible,” Hensinger said.
Still both Hensinger and Ricciuti agree the developments by Google add to the excitement around quantum computing and continued development in the space.
“This result increases confidence further that humanity will be able to build practical quantum computers enabling some of the high impactful applications quantum computers are known for,” Hensinger said.
Global investors are bracing for a battle between long and short-term wins amid a dramatic sell-off in artificial intelligence-related stocks.
AI darling Nvidia buoyed an otherwise deflated market when it reported strong earnings after the bell on Wednesday, sending its own stock soaring and carrying related names alongside it. However, the rally quickly reversed on Thursday with Nvidia ultimately ending the trading session 3% lower.
While the U.S. chipmaker’s earnings initially appeared strong enough to quell concerns over an AI bubble, economic speculation put global investors back on the defensive as hopes dimmed of a December rate cut by the Federal Reserve. The U.K.’s hotly anticipated Autumn Budget is also expected next week.
“I think the market is quite confused as to why this is happening,” Ozan Ozkural, founding managing partner at Tanto Capital Partners, told CNBC’s “Squawk Box Europe” on Friday.
Market moves this year have been driven by sentiment, momentum, AI and innovation, “with sprinkles of geopolitical risk,” he said. “Although we haven’t got a specific reason why there has been a sell-off on the back of the strong Nvidia results, to me it’s not that surprising, because [it’s] only a matter of time until sentiment just shifts, because we just live in a much more uncertain world.”
There also doesn’t need to be a catalyst, he added. However, the “most dangerous place we can be at” is a sustained sell-off, even if it’s a slow burn, Ozkural warning, noting that this could lead portfolio managers to lock in gains and cash out.
Asset managers are driven by compensation cycles which is why they don’t like to hedge their bets, he said. “No one cares about the long term. Everyone is dead in the long term. No one even cares about the medium term. It’s all about short term cycles,” he said.
“But the reality is, it’s year end, people need to get paid their bonuses, and it doesn’t pay to be bearish unless we see a sustained level of a sell-off.”
Investors with cash in an AI ETF or index may be cashing out due to a mixture of year-end risk management and continued concerns over an AI bubble. Those who may have made a lot of money on the back of the AI trade will probably want to step back and sell, said Stephen Yiu, investment chief at Blue Whale Growth Fund, which has a position in Nvidia.
However, for Julius Bendikas, European head of macro and dynamic asset allocation at Mercer, “it’s the battle between the solid fundamentals and questions being raised about multiples and maybe positioning getting a touch stretched.”
Despite solid fundamentals and earnings exceeding expectations, Bendikas told CNBC’s “Europe Early Edition” that investors are now starting to question whether the price is right and have started to sell as a result.
On technicals, “arguably, a lot of people have rushed into equities,” he said, noting that a recent Bank of America survey found cash levels are low. “So people have been quite long equities, maybe too long equities. And I think what we’ve seen yesterday is the valuations and technicals [narrative] overpowering the fundamental narrative, which came in quite strong post the Nvidia earnings overnight, a day ago.”
Nick Patience, AI lead at The Futurum Group, added: “Investors are also concerned about the circular nature of deals between Nvidia and other ecosystem players, questioning whether massive capital expenditures from hyperscaler customers represent sustainable demand.”
Fed rate cut
The moves may also reflect economic pressure. “The [Thursday] afternoon decline coincided with some negative macroeconomic signals in the form of the delayed September jobs report released in the morning that showed the US economy added 119,000 jobs – more than the expected 50,000 – but the unemployment rate rose to 4.4%, the highest level since October 2021,” Patience said.
The last bit of big news the market is expecting is the Fed’s December rate decision; investors had anticipated a cut but are now split on whether it will happen.
The central bank opting to not cut rates is “not an issue,” Yiu said, but could lead investors who had expected it to cut, to pause and recalibrate ahead of next year.
“I think people just want to probably lock in and derisk, and take a break from [President Donald] Trump as well, who knows what Trump is going to next,” he added.
Amid the hype, it’s difficult to work out the AI winners and losers, Yiu said, but he expects a differentiation between the companies investing in AI and those on the receiving end of that cash, which he called AI infrastructure. As the market shakes out, Yiu is placing his bets on the latter.
The entrance to a Foxconn construction site in Mount Pleasant, Wisconsin, in May 2019.
Katie Tarasov | CNBC
Foxconn showcased its push into artificial intelligence at its annual ‘Hon Hai Tech Day’ in Taiwan on Friday, underscoring the world’s largest contract manufacturer’s efforts to evolve beyond its role as the biggest assembler of Apple’s iPhones.
The company, officially known as Hon Hai Precision Industry Co., has also become a major player in the AI hardware space, with its event taking place the same day it announced a partnership with ChatGPT maker OpenAI.
OpenAI CEO Sam Altman, in a video statement streamed at the event, said that the two firms would “share insight into emerging hardware needs across the AI industry.”
He added that Foxconn would use those insights to design and prototype new equipment that could be manufactured in the United States.
The partnership will center on Foxconn’s server business, which earlier this year became its largest revenue driver and helped drive record profit in the September quarter.
Describing Foxconn and OpenAI as “natural partners,” Kirk Yang, an adjunct finance professor at National Taiwan University, told CNBC, “OpenAI needs strong partners, not only to manufacture products, but to quickly introduce all the products to the market.”
“So I think it makes perfect sense for OpenAI to work with Foxconn. And Foxconn is probably the strongest partner that open AI can find,” he added.
Foxconn also announced a partnership with Intrinsic, a unit of Alphabet to build so-called “artificial intelligence factories.”
The Taiwanese manufacturer highlighted deeper work with Nvidia as well, showcasing its compute trays for the chip designer’s cutting-edge Blackwell chips.
Speaking at the Friday event, Alexis Bjorlin, vice president and general manager of Nvidia’s DGX Cloud unit, said the partners would work on deploying advanced AI infrastructure much faster to meet customer demand.
Despite Nvidia’s results showing that demand for AI hardware remains strong, concerns persist in the market about a potential AI bubble and the sustainability of heavy AI spending.
Speaking to CNBC’s Emily Chan on the sidelines of Hon Hai Tech Day, Foxconn Chairman Young Liu expressed confidence that the company would be protected from a potential AI bubble.
“No matter what [AI] models or [AI] model players will win, they all need hardware, and no matter what GPU player will win, they all need system and component suppliers to support them,” he said.
The logo of Japanese company SoftBank Group is seen outside the company’s headquarters in Tokyo on January 22, 2025.
Kazuhiro Nogi | Afp | Getty Images
A sector-wide pullback hit Asian chip stocks Friday, led by a steep decline in SoftBank, after Nvidia‘s sharp drop overnight defied its stronger-than-expected earnings and bullish outlook.
SoftBank plunged more than 10% in Tokyo. The Japanese tech conglomerate recently offloaded its Nvidia shares but still controls British semiconductor company Arm, which supplies Nvidia with chip architecture and designs.
SoftBank is also involved in a number of AI ventures that use Nvidia’s technology, including the $500 billion Stargate project for data centers in the U.S.
South Korea’s SK Hynix fell nearly 10%. The memory chip maker is Nvidia’s top supplier of high-bandwidth memory used in AI applications. Samsung Electronics, a rival that also supplies Nvidia with memory, fell over 5%.
Taiwan’s Hon Hai Precision Industry, also known as Foxconn, which manufactures server racks designed for AI workloads, dipped 4%.
The retreat in major Asian semiconductor giants comes after Nvidia fell over 3% in the U.S. on Thursday, despite beating Wall Street expectations in its third-quarter earnings the night before.
The company also provided stronger-than-expected fourth-quarter sales guidance, which analysts said could lift earnings expectations across the sector.
However, smaller chip players in Asia were not spared either.
In Tokyo, Renesas Electronics, a key Nvidia supplier, fell 2.3%. Tokyo Electron, which provides essential chipmaking equipment to foundries that manufacture Nvidia’s chips, was down 5.32%.
Another Japanese chip equipment maker, Lasertec, was down over 3.5%.