Computer scientists are questioning whether Alphabet’s DeepMind will ever make A.I. more human-like

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4 years ago

June 18, 2021

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David Silver, leader of the reinforcement learning research group at DeepMind, being awarded an honorary “ninth dan” professional ranking for AlphaGo.

JUNG YEON-JE | AFP | Getty Images

Computer scientists are questioning whether DeepMind, the Alphabet-owned U.K. firm that’s widely regarded as one of the world’s premier AI labs, will ever be able to make machines with the kind of “general” intelligence seen in humans and animals.

In its quest for artificial general intelligence, which is sometimes called human-level AI, DeepMind is focusing a chunk of its efforts on an approach called “reinforcement learning.”

This involves programming an AI to take certain actions in order to maximize its chance of earning a reward in a certain situation. In other words, the algorithm “learns” to complete a task by seeking out these preprogrammed rewards. The technique has been successfully used to train AI models how to play (and excel at) games like Go and chess. But they remain relatively dumb, or “narrow.” DeepMind’s famous AlphaGo AI can’t draw a stickman or tell the difference between a cat and a rabbit, for example, while a seven-year-old can.

Despite this, DeepMind, which was acquired by Google in 2014 for around $600 million, believes that AI systems underpinned by reinforcement learning could theoretically grow and learn so much that they break the theoretical barrier to AGI without any new technological developments.

Researchers at the company, which has grown to around 1,000 people under Alphabet’s ownership, argued in a paper submitted to the peer-reviewed Artificial Intelligence journal last month that “Reward is enough” to reach general AI. The paper was first reported by VentureBeat last week.

In the paper, the researchers claim that if you keep “rewarding” an algorithm each time it does something you want it to, which is the essence of reinforcement learning, then it will eventually start to show signs of general intelligence.

“Reward is enough to drive behavior that exhibits abilities studied in natural and artificial intelligence, including knowledge, learning, perception, social intelligence, language, generalization and imitation,” the authors write.

“We suggest that agents that learn through trial and error experience to maximize reward could learn behavior that exhibits most if not all of these abilities, and therefore that powerful reinforcement learning agents could constitute a solution to artificial general intelligence.”

Not everyone is convinced, however.

Samim Winiger, an AI researcher in Berlin, told CNBC that DeepMind’s “reward is enough” view is a “somewhat fringe philosophical position, misleadingly presented as hard science.”

He said the path to general AI is complex and that the scientific community is aware that there are countless challenges and known unknowns that “rightfully instill a sense of humility” in most researchers in the field and prevent them from making “grandiose, totalitarian statements” such as “RL is the final answer, all you need is reward.”

DeepMind told CNBC that while reinforcement learning has been behind some of its most well-known research breakthroughs, the AI technique accounts for only a fraction of the overall research it carries out. The company said it thinks it’s important to understand things at a more fundamental level, which is why it pursues other areas such as “symbolic AI” and “population-based training.”

“In somewhat typical DeepMind fashion, they chose to make bold statements that grabs attention at all costs, over a more nuanced approach,” said Winiger. “This is more akin to politics than science.”

Stephen Merity, an independent AI researcher, told CNBC that there’s “a difference between theory and practice.” He also noted that “a stack of dynamite is likely enough to get one to the moon, but it’s not really practical.”

Ultimately, there’s no proof either way to say whether reinforcement learning will ever lead to AGI.

Rodolfo Rosini, a tech investor and entrepreneur with a focus on AI, told CNBC: “The truth is nobody knows and that DeepMind’s main product continues to be PR and not technical innovation or products.”

Entrepreneur William Tunstall-Pedoe, who sold his Siri-like app Evi to Amazon, told CNBC that even if the researchers are correct “that doesn’t mean we will get there soon, nor does it mean that there isn’t a better, faster way to get there.”

DeepMind’s “Reward is enough” paper was co-authored by DeepMind heavyweights Richard Sutton and David Silver, who met DeepMind CEO Demis Hassabis at the University of Cambridge in the 1990s.

“The key problem with the thesis put forth by ‘Reward is enough’ is not that it is wrong, but rather that it cannot be wrong, and thus fails to satisfy Karl Popper’s famous criterion that all scientific hypotheses be falsifiable,” said a senior AI researcher at a large U.S. tech firm, who wished to remain anonymous due to the sensitive nature of the discussion.

“Because Silver et al. are speaking in generalities, and the notion of reward is suitably underspecified, you can always either cherry pick cases where the hypothesis is satisfied, or the notion of reward can be shifted such that it is satisfied,” the source added.

“As such, the unfortunate verdict here is not that these prominent members of our research community have erred in any way, but rather that what is written is trivial. What is learned from this paper, in the end? In the absence of practical, actionable consequences from recognizing the unalienable truth of this hypothesis, was this paper enough?”

What is AGI?

While AGI is often referred to as the holy grail of the AI community, there’s no consensus on what AGI actually is. One definition is it’s the ability of an intelligent agent to understand or learn any intellectual task that a human being can.

But not everyone agrees with that and some question whether AGI will ever exist. Others are terrified about its potential impacts and whether AGI would build its own, even more powerful, forms of AI, or so-called superintelligences.

Ian Hogarth, an entrepreneur turned angel investor, told CNBC that he hopes reinforcement learning isn’t enough to reach AGI. “The more that existing techniques can scale up to reach AGI, the less time we have to prepare AI safety efforts and the lower the chance that things go well for our species,” he said.

Winiger argues that we’re no closer to AGI today than we were several decades ago. “The only thing that has fundamentally changed since the 1950/60s, is that science-fiction is now a valid tool for giant corporations to confuse and mislead the public, journalists and shareholders,” he said.

Fueled with hundreds of millions of dollars from Alphabet every year, DeepMind is competing with the likes of Facebook and OpenAI to hire the brightest people in the field as it looks to develop AGI. “This invention could help society find answers to some of the world’s most pressing and fundamental scientific challenges,” DeepMind writes on its website.

DeepMind COO Lila Ibrahim said on Monday that trying to “figure out how to operationalize the vision” has been the biggest challenge since she joined the company in April 2018.

Technology

AppLovin and Robinhood added to S&P 500

Published

2 days ago

September 5, 2025

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Shares of advertising technology company AppLovin and stock trading app Robinhood Markets each jumped about 7% in extended trading on Friday after S&P Global said the two will join the S&P 500 index.

The changes will go into effect before the beginning of trading on Sept. 22, S&P Global announced in a statement. AppLovin will replace MarketAxess Holdings, while Robinhood will take the place of Caesars Entertainment.

In March, short-seller Fuzzy Panda Research advised the committee for the large-cap U.S. index to keep AppLovin from becoming a constituent. AppLovin shares dropped 15% in December, when the committee picked Workday to join the S&P 500. Robinhood, for its part, saw shares slip 2% in June when it was excluded from a quarterly rebalancing of the index.

The S&P 500 already has a heavy concentration of large technology companies. Datadog and DoorDash entered earlier this year.

It’s normal for stocks to go up on news of their inclusion in a major index such as the S&P 500. Fund managers need to buy shares to reflect the updates.

FTC commissioner questions status of Snap AI chatbot complaint: ‘People deserve answers’

Published

2 days ago

September 5, 2025

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FTC commissioner questions status of Snap AI chatbot complaint: 'People deserve answers'

FTC Commissioner Rebecca Slaughter on President Trump's latest attempt to fire her

U.S. Federal Trade Commission Commissioner Rebecca Slaughter raised questions on Friday about the status of an artificial intelligence chatbot complaint against Snap that the agency referred to the Department of Justice earlier this year.

In January, the FTC announced that it would refer a non-public complaint regarding allegations that Snap’s My AI chatbot posed potential “risks and harms” to young users and said it would refer the suit to the DOJ “in the public interest.”

“We don’t know what has happened to that complaint,” Slaughter said on CNBC’s ‘The Exchange.” “The public does not know what has happened to that complaint, and that’s the kind of thing that I think people deserve answers on.”

Snap’s My AI chatbot, which debuted in 2023, is powered by large language models from OpenAI and Google and has drawn scrutiny for problematic responses.

The DOJ did not immediately respond to a request for comment. Snap declined to comment.

Slaugther’s comments came a day after President Donald Trump held a White House dinner with several tech executives, including Google CEO Sundar Pichai, Meta CEO Mark Zuckerberg and Apple CEO Tim Cook.

Google leads monster week for tech, pushing megacaps to combined $21 trillion in market cap

Published

2 days ago

September 5, 2025

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Google leads monster week for tech, pushing megacaps to combined trillion in market cap

Alphabet and Google CEO Sundar Pichai meets with Polish Prime Minister Donald Tusk at Google for Startups in Warsaw, Poland, on February 13, 2025.

Klaudia Radecka | Nurphoto | Getty Images

From the courtroom to the boardroom, it was a big week for tech investors.

The resolution of Google’s antitrust case led to sharp rallies for Alphabet and Apple. Broadcom shareholders cheered a new $10 billion customer. And Tesla’s stock was buoyed by a freshly proposed pay package for CEO Elon Musk.

Add it up, and the U.S. tech industry’s eight trillion-dollar companies gained a combined $420 billion in market cap this week, lifting their total value to $21 trillion, despite a slide in Nvidia shares.

Those companies now account for roughly 36% of the S&P 500, a proportion so great by historical standards that Howard Silverblatt, senior index analyst at S&P Dow Jones Indices, told CNBC by email, “there are no comparisons.”

Broadcom pops

Broadcom shares spike briefly on Q4 beat

While OpenAI was an indirect catalyst for Google and Apple this week, it was more directly tied to the huge rally in Broadcom’s stock.

Following Broadcom’s better-than-expected earnings report on Thursday, CEO Hock Tan told analysts that his chipmaker had secured a $10 billion contract with a new customer, which would be the company’s fourth large AI client.

Several analysts said the new customer is OpenAI, and the Financial Times reported on a partnership between the two companies.

Broadcom is the newest entrant into the trillion-dollar club, thanks to the company’s custom chips for AI, already used by Google, Meta and TikTok parent ByteDance. With Its 13% jump this week, the stock is now up 120% in the past year, lifting Broadcom’s market cap to around $1.6 trillion.

“The company is firing on all cylinders with clear line of sight for growth supported by significant backlog,” analysts at Barclays wrote in a note, maintaining their buy recommendation and lifting their price target on the stock.

For the other giant AI chipmaker, the past week wasn’t so good.

Nvidia shares fell more than 4% in the holiday-shortened week, the worst performance among the megacaps. There was no apparent negative news for Nvidia, but the stock has now dropped for four consecutive weeks.

Still, Nvidia remains the largest company by market cap, valued at over $4 trillion, with its stock up 56% in the past 12 months.

Microsoft also fell this week and is on an extended slide, dropping for five straight weeks. Shares are still up 21% over the last 12 months.

On the flipside, Tesla has been the laggard in the group. Shares of the electric vehicle maker are down 13% this year due to a multi-quarter sales slump that reflects rising competition from lower-cost Chinese manufacturers and an aging lineup of EVs.

But Tesla shares climbed 5% this week, sparked mostly by gains on Friday after the company said it wants investors to approve a pay plan for Musk that could be worth up to almost $1 trillion.

The payouts, split into 12 tranches, would require Tesla to see significant value appreciation, starting with the first award that won’t kick in until the company almost doubles its market cap to $2 trillion.

Tesla Chairwoman Robyn Denholm told CNBC’s Andrew Ross Sorkin the plan was designed to keep Musk, the world’s richest person, “motivated and focused on delivering for the company.”

WATCH: Tesla board chair on Elon Musk’s pay plan