Meta’s AI chief doesn’t think AI super intelligence is coming anytime soon, and is skeptical on quantum computing
Yann LeCun, chief AI scientist at Meta, speaks at the Viva Tech conference in Paris, June 13, 2023.
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Meta’s chief scientist and deep learning pioneer Yann LeCun said he believes that current AI systems are decades away from reaching some semblance of sentience, equipped with common sense that can push their abilities beyond merely summarizing mountains of text in creative ways.
His point of view stands in contrast to that of Nvidia CEO Jensen Huang, who recently said AI will be “fairly competitive” with humans in less than five years, besting people at a multitude of mentally intensive tasks.
“I know Jensen,” LeCun said at a recent event highlighting the Facebook parent company’s 10-year anniversary of its Fundamental AI Research team. LeCun said the Nvidia CEO has much to gain from the AI craze. “There is an AI war, and he’s supplying the weapons.”
“[If] you think AGI is in, the more GPUs you have to buy,” LeCun said, about technologists attempting to develop artificial general intelligence, the kind of AI on par with human-level intelligence. As long as researchers at firms such as OpenAI continue their pursuit of AGI, they will need more of Nvidia’s computer chips.
Society is more likely to get “cat-level” or “dog-level” AI years before human-level AI, LeCun said. And the technology industry’s current focus on language models and text data will not be enough to create the kinds of advanced human-like AI systems that researchers have been dreaming about for decades.
“Text is a very poor source of information,” LeCun said, explaining that it would likely take 20,000 years for a human to read the amount of text that has been used to train modern language models. “Train a system on the equivalent of 20,000 years of reading material, and they still don’t understand that if A is the same as B, then B is the same as A.”
“There’s a lot of really basic things about the world that they just don’t get through this kind of training,” LeCun said.
Hence, LeCun and other Meta AI executives have been heavily researching how the so-called transformer models used to create apps such as ChatGPT could be tailored to work with a variety of data, including audio, image and video information. The more these AI systems can discover the likely billions of hidden correlations between these various kinds of data, the more they could potentially perform more fantastical feats, the thinking goes.
Some of Meta’s research includes software that can help teach people how to play tennis better while wearing the company’s Project Aria augmented reality glasses, which blend digital graphics into the real world. Executives showed a demo in which a person wearing the AR glasses while playing tennis was able to see visual cues teaching them how to properly hold their tennis rackets and swing their arms in perfect form. The kinds of AI models needed to power this type of digital tennis assistant require a blend of three-dimensional visual data in addition to text and audio, in case the digital assistant needs to speak.
These so-called multimodal AI systems represent the next frontier, but their development won’t come cheap. And as more companies such as Meta and Google parent Alphabet research more advanced AI models, Nvidia could stand to gain even more of an edge, particularly if no other competition emerges.
The AI hardware of the future
Nvidia has been the biggest benefactor of generative AI, with its pricey graphics processing units becoming the standard tool used to train massive language models. Meta relied on 16,000 Nvidia A100 GPUs to train its Llama AI software.
CNBC asked if the tech industry will need more hardware providers as Meta and other researchers continue their work developing these kinds of sophisticated AI models.
“It doesn’t require it, but it would be nice,” LeCun said, adding that the GPU technology is still the gold standard when it comes to AI.
Still, the computer chips of the future may not be called GPUs, he said.
“What you’re going to see hopefully emerging are new chips that are not graphical processing units, they are just neural, deep learning accelerators,” LeCun said.
LeCun is also somewhat skeptical about quantum computing, which tech giants such as Microsoft, IBM, and Google have all poured resources into. Many researchers outside Meta believe quantum computing machines could supercharge advancements in data-intensive fields such as drug discovery, as they’re able to perform multiple calculations with so-called quantum bits as opposed to conventional binary bits used in modern computing.
But LeCun has his doubts.
“The number of problems you can solve with quantum computing, you can solve way more efficiently with classical computers,” LeCun said.
“Quantum computing is a fascinating scientific topic,” LeCun said. It’s less clear about the “practical relevance and the possibility of actually fabricating quantum computers that are actually useful.”
Meta senior fellow and former tech chief Mike Schroepfer concurred, saying that he evaluates quantum technology every few years and believes that useful quantum machines “may come at some point, but it’s got such a long time horizon that it’s irrelevant to what we’re doing.”
“The reason we started an AI lab a decade ago was that it was very obvious that this technology is going to be commercializable within the next years’ time frame,” Schroepfer said.
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Chuck Robbins, chief executive officer of Cisco, participates in a Bloomberg interview at the World Economic Forum in Davos, Switzerland, on Jan. 17, 2024.
Stefan Wermuth | Bloomberg | Getty Images
Few companies were as hot in early 2000 as Cisco, whose networking equipment served as the backbone of the internet boom.
On Wednesday, Cisco’s stock surpassed its dot-com peak for the first time. The shares rose almost 1% to $80.25, topping their prior split-adjusted record or $80.06 reached on March 27, 2000. That’s the same day that Cisco passed Microsoft to become the most valuable publicly traded company in the world.
Back then, investors saw Cisco as a way to bet on the growth of the web, as companies that wanted to get online relied upon the hardware maker’s switches and routers. But following a half-decade boom, the dot-com bubble burst just after Cisco reached its zenith, a collapse that wiped out more than three-quarters of the Nasdaq’s value by October 2002.
While the market swoon eliminated scores of internet highflyers, Cisco survived the upheaval. Eventually it started to grow and expand, diversifying through a series of acquisitions like set-top box maker Scientific- Atlanta in 2006, followed by software companies including Webex, AppDynamics, Duo and Splunk.
With its gains on Wednesday, Cisco’s market cap sits at $317 billion, making it only the 13th most valuable U.S. tech company. In recent years, the stock has badly trailed tech’s megacaps, which have been at the center of the new boom surrounding artificial intelligence.
The AI market has reached a level of euphoria that many analysts have compared to the dot-com era. Instead of Cisco, the modern infrastructure winner is Nvidia, whose AI chips are at the heart of model development and are relied up by the other major tech companies that are all building out AI-focused data centers. Nvidia has a market cap of $4.5 trillion, roughly 14 times Cisco’s current value.
But Cisco is angling to benefit from the AI craze, with CEO Chuck Robbins in November touting $1.3 billion in quarterly AI infrastructure orders from large web companies. Total revenue approached $15 billion, which was up 7.5% year over year, compared with 66% growth in 2000.
Shares of Cisco are up about 36% so far in 2025, outperforming the Nasdaq, which has gained about 22% over the same period.
WATCH: Cisco CEO on latest quarter: AI demand from hyperscalers is accelerating
Larry Ellison, Oracle’s co-founder and chief technology officer, appears at the Formula One British Grand Prix in Towcester, U.K., on July 6, 2025.
Jay Hirano | Sopa Images | Lightrocket | Getty Images
Oracle is scheduled to report fiscal second-quarter results after market close on Wednesday.
Here’s what analysts are expecting, according to LSEG:
- Earnings per share: $1.64 adjusted
- Revenue: $16.21 billion
Wall Street expects revenue to increase 15% in the quarter that ended Nov. 30, from $14.1 billion a year earlier. Analysts polled by StreetAccount are looking for $7.92 billion in cloud revenue and $6.06 billion from software.
The report lands at a critical moment for Oracle, which has tried to position itself at the center of the artificial intelligence boom by committing to massive build-outs. While the move has been a boon for Oracle’s revenue and its backlog, investors have grown concerned about the amount of debt the company is raising and the risks it faces should the AI market slow.
The stock plummeted 23% in November, its worst monthly performance since 2001 and, as of Tuesday’s close, is 33% below its record reached in September. Still, the shares are up 33% for the year, outperforming the Nasdaq, which has gained 22% over that stretch.
Over the past decade, Oracle has diversified its business beyond databases and enterprise software and into cloud infrastructure, where it competes with Amazon, Microsoft and Google. Those companies are all vying for big AI contracts and are investing heavily in data centers and hardware necessary to meet expected demand.
OpenAI, which sparked the generative AI rush with the launch of ChatGPT three years ago, has committed to spending more than $300 billion on Oracle’s infrastructure services over five years.
“Oracle’s job is not to imagine gigawatt-scale data centers. Oracle’s job is to build them,” Larry Ellison, the company’s co-founder and chairman, told investors in September.
Oracle raised $18 billion during the period, one of the biggest issuances on record for a tech company. Skeptical investors have been buying five-year credit default swaps, driving them to multiyear highs. Credit default swaps are like insurance for investors, with buyers paying for protection in case the borrower can’t repay its debt.
“Customer concentration is a major issue here, but I think the bigger thing is, How are they going to pay for this?” said RBC analyst Rishi Jaluria, who has the equivalent of a hold rating on Oracle’s stock.
During the quarter, Oracle named executives Clay Magouyrk and Mike Sicilia as the company’s new CEOs, succeeding Safra Catz. Oracle also introduced AI agents for automating various facets of finance, human resources and sales.
Executives will discuss the results and issue guidance on a conference call starting at 5 p.m. ET.
WATCH: Oracle’s debt concerns loom large ahead of quarterly earnings
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