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.
Chesnot | Getty Images News | Getty Images
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.
WATCH: Meta on the defensive amid reports of Instagram’s harm
The Datadog stand is being displayed on day one of the AWS Summit Seoul 2024 at the COEX Convention and Exhibition Center in Seoul, South Korea, on May 16, 2024.
Chris Jung | Nurphoto | Getty Images
Datadog shares were up 10% in extended trading on Wednesday after S&P Global said the monitoring software provider will replace Juniper Networks in the S&P 500 U.S. stock index.
S&P Global is making the change effective before the beginning of trading on July 9, according to a statement.
Computer server maker Hewlett Packard Enterprise, also a constituent of the index, said earlier on Wednesday that it had completed its acquisition of Juniper, which makes data center networking hardware. HPE disclosed in a filing that it paid $13.4 billion to Juniper shareholders.
Over the weekend, the two companies reached a settlement with the U.S. Justice Department, which had sued in opposition to the deal. As part of the settlement, HPE agreed to divest its global Instant On campus and branch business.
While tech already makes up an outsized portion of the S&P 500, the index has has been continuously lifting its exposure as the industry expands into more areas of society.
DoorDash was the latest tech company to join during the last rebalancing in March. Cloud software vendor Workday was added in December, and that was preceded earlier in 2024 with the additions of Palantir, Dell, CrowdStrike, GoDaddy and Super Micro Computer.
Stocks often rally when they’re added to a major index, as fund managers need to rebalance their portfolios to reflect the changes.
New York-based Datadog went public in 2019. The company generated $24.6 million in net income on $761.6 million in revenue in the first quarter of 2025, according to a statement. Competitors include Cisco, which bought Splunk last year, as well as Elastic and cloud infrastructure providers such as Amazon and Microsoft.
Datadog has underperformed the broader tech sector so far this year. The stock was down 5.5% as of Wednesday’s close, while the Nasdaq was up 5.6%. Still, with a market cap of $46.6 billion, Datadog’s valuation is significantly higher than the median for that index.
— CNBC’s Ari Levy contributed to this report.
CNBC: Datadog CEO Olivier Pomel on the cloud computing outlook
A representation of cryptocurrency Ethereum is placed on a PC motherboard in this illustration taken on June 16, 2023.
Dado Ruvic | Reuters
Stocks tied to the price of ether, better known as ETH, were higher on Wednesday, reflecting renewed enthusiasm for the crypto asset amid a surge of interest in stablecoins and tokenization.
BitMine Immersion Technologies, a bitcoin miner that announced plans this week to make ETH its primary treasury reserve asset, jumped about 20%. It’s gained more than 1,000% since the announcement. Betting platform SharpLink Gaming, which has also initiated an ETH treasury strategy, added more than 11%. Bit Digital, which last week exited bitcoin mining to focus on its ETH treasury and staking plans, jumped more than 6%.
“We’re finally at the point where real use cases are emerging, and stablecoins have been the first version of that at scale but they’re going to open the door to a much bigger story around tokenizing other assets and using digital assets in new ways,” Devin Ryan, head of financial technology research at Citizens.
On Tuesday, as bitcoin ETFs snapped a 15-day streak of inflows, ether ETFs saw $40 million in inflows led by BlackRock’s iShares Ethereum Trust. ETH ETFs came back to life in June after much concern that they were becoming zombie funds.
The price of the coin itself was last higher by 5%, according to Coin Metrics, though it’s still down 24% this year.
Ethereum has been struggling with an identity crisis fueled by uncertainty about the network’s value proposition, weaker revenue since its last big technical upgrade and increasing competition from Solana. Market volatility, driven by geopolitical uncertainty this year, has not helped.
The Ethereum network’s smart contracts capability makes it a prominent platform for the tokenization of traditional assets, which includes U.S. dollar-pegged stablecoins. Fundstrat’s Tom Lee this week called Ethereum “the backbone and architecture” of stablecoins. Both Tether (USDT) and Circle‘s USD Coin (USDC) are issued on the network.
BlackRock’s tokenized money market fund (known as BUIDL, which stands for USD Institutional Digital Liquidity Fund) also launched on Ethereum last year before expanding to other blockchain networks.
Tokenization is the process of issuing digital representations on a blockchain network of publicly traded securities, real world assets or any other form of value. Holders of tokenized assets don’t have outright ownership of the assets themselves.
The latest wave of interest in ETH-related assets follows an announcement by Robinhood this week that it will enable trading of tokenized U.S. stocks and ETFs across Europe, after a groundswell of interest in stablecoins throughout June following Circle’s IPO and the Senate passage of its proposed stablecoin bill, the GENIUS Act.
Ether, which turns 10 years old at the end of July, is sitting about 75% off its all-time high.
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