Geoffrey Hinton hopes the prize will add credibility to his claims about the dangers of AI technology he pioneered
4 min
The newly minted Nobel laureate Geoffrey Hinton has a message about the artificial-intelligence systems he helped create: get more serious about safety or they could endanger humanity.
“I think we’re at a kind of bifurcation point in history where, in the next few years, we need to figure out if there’s a way to deal with that threat,” Hinton said in an interview Tuesday with a Nobel Prize official that mixed pride in his life’s work with warnings about the growing danger it poses.
The 76-year-old Hinton resigned from Google last year in part so he could talk more about the possibility that AI systems could escape human control and influence elections or power dangerous robots. Along with other experienced AI researchers, he has called on such companies as OpenAI, Meta Platforms and Alphabet -owned Google to devote more resources to the safety of the advanced systems that they are competing against each other to develop as quickly as possible.
Hinton’s Nobel win has provided a new platform for his doomsday warnings at the same time it celebrates his critical role in advancing the technologies fuelling them. Hinton has argued that advanced AI systems are capable of understanding their outputs, a controversial view in research circles.
“Hopefully, it will make me more credible when I say these things really do understand what they’re saying,” he said of the prize.
Hinton’s views have pitted him against factions of the AI community that believe dwelling on doomsday scenarios needlessly slows technological progress or distracts from more immediate harms, such as discrimination against minority groups .
“I think that he’s a smart guy, but I think a lot of people have way overhyped the risk of these things, and that’s really convinced a lot of the general public that this is what we should be focusing on, not the more immediate harms of AI,” said Melanie Mitchell, a professor at the Santa Fe Institute, during a panel last year.
Hinton visited Google’s Silicon Valley headquarters Tuesday for an informal celebration, and some of the company’s top AI executives congratulated him on social media.
On Wednesday, other prominent Googlers specialising in AI were also awarded a Nobel Prize . Demis Hassabis, chief executive of Google DeepMind, and John M. Jumper, director at the AI lab, were part of a group of three scientists who won the chemistry prize for their work on predicting the shape of proteins.
Hinton is sharing the Nobel Prize in physics with John Hopfield of Princeton University for their work since the 1980s on neural networks that process information in ways inspired by the human brain. That work is the basis for many of the AI technologies in use today, from ChatGPT’s humanlike conversations to Google Photos’ ability to recognize who is in every picture you take.
“Their contributions to connect fundamental concepts in physics with concepts in biology, not just AI—these concepts are still with us today,” said Yoshua Bengio , an AI researcher at the University of Montreal.
In 2012, Hinton worked with two of his University of Toronto graduate students, Alex Krizhevsky and Ilya Sutskever, on a neural network called AlexNet programmed to recognise images in photos. Until that point, computer algorithms had often been unable to tell that a picture of a dog was really a dog and not a cat or a car.
AlexNet’s blowout victory at a 2012 contest for image-recognition technology was a pivotal moment in the development of the modern AI boom, as it proved the power of neural nets over other approaches.
That same year, Hinton started a company with Krizhevsky and Sutskever that turned out to be short-lived. Google acquired it in 2013 in an auction against competitors including Baidu and Microsoft, paying $44 million essentially to hire the three men, according to the book “Genius Makers.” Hinton began splitting time between the University of Toronto and Google, where he continued research on neural networks.
Hinton is widely revered as a mentor for the current generation of top AI researchers including Sutskever, who co-founded OpenAI before leaving this spring to start a company called Safe Superintelligence.
Hinton received the 2018 Turing Award, a computer-science prize, for his work on neural networks alongside Bengio and a fellow AI researcher, Yann LeCun . The three are often referred to as the modern “godfathers of AI.”
By 2023, Hinton had become alarmed about the consequences of building more powerful artificial intelligence. He began talking about the possibility that AI systems could escape the control of their creators and cause catastrophic harm to humanity. In doing so, he aligned himself with a vocal movement of people concerned about the existential risks of the technology.
“We’re in a situation that most people can’t even conceive of, which is that these digital intelligences are going to be a lot smarter than us, and if they want to get stuff done, they’re going to want to take control,” Hinton said in an interview last year.
Hinton announced he was leaving Google in spring 2023, saying he wanted to be able to freely discuss the dangers of AI without worrying about consequences for the company. Google had acted “very responsibly,” he said in an X post.
In the subsequent months, Hinton has spent much of his time speaking to policymakers and tech executives, including Elon Musk , about AI risks.
Hinton cosigned a paper last year saying companies doing AI work should allocate at least one-third of their research and development resources to ensuring the safety and ethical use of their systems.
“One thing governments can do is force the big companies to spend a lot more of their resources on safety research, so that for example companies like OpenAI can’t just put safety research on the back burner,” Hinton said in the Nobel interview.
An OpenAI spokeswoman said the company is proud of its safety work.
With Bengio and other researchers, Hinton supported an artificial-intelligence safety bill passed by the California Legislature this summer that would have required developers of large AI systems to take a number of steps to ensure they can’t cause catastrophic damage. Gov. Gavin Newsom recently vetoed the bill , which was opposed by most big tech companies including Google.
Hinton’s increased activism has put him in opposition to other respected researchers who believe his warnings are fantastical because AI is far from having the capability to cause serious harm.
“Their complete lack of understanding of the physical world and lack of planning abilities put them way below cat-level intelligence, never mind human-level,” LeCun wrote in a response to Hinton on X last year.
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Wall Street’s hottest momentum trade has reversed sharply, as former winners tumble and heavily shorted stocks surge.
3 min
Wall Street’s hottest trade has gone ice cold.
For years, it paid off to buy stocks that were rising in price—and bet against struggling shares. The momentum trade was especially profitable this year, as investors piled into hot stocks including Micron Technology, Nvidia, Advanced Micro Devices and other artificial-intelligence darlings while wagering against those likely to be hurt by the embrace of AI.
The S&P 500 Momentum Index soared 44% in the second quarter, its best quarterly performance on record, and it surged 133% over the past five years, nearly double the broad market’s performance.
Mega funds and rookie investors alike piled into the trade, some using leverage and options contracts in an effort to amplify their returns, propelling the underlying shares higher.
“It is a self-fulfilling prophecy,” said Matthew Tym, managing director at Cantor Fitzgerald, of the trade.
Suddenly, the trade is a loser. The momentum index has tumbled more than 9% since July 1, lagging behind the S&P 500’s 2.8% gain. The index—which tracks stocks in the S&P 500 based on a “momentum score”—is on track for the biggest quarterly underperformance in 25 years. July was the second-worst month for the momentum trade in around 40 years, according to Bank of America estimates; the only month worse was April 2009, in the teeth of the global financial crisis.
Hedge funds that bought momentum shares while shorting low-momentum stocks suffered even more. At the same time, a basket of the most popular stocks held by hedge funds tracked by Goldman Sachs recorded its biggest one-month underperformance in July relative to the S&P 500 in more than 20 years, according to the bank’s analysts.
Momentum trading is based on a rather simple observation: Investments that go up tend to keep outperforming; those that underperform often remain laggards. This kind of trading might seem too simple a stock-picking strategy to work. Yet it often has.
“For decades, it didn’t take a lot of sophistication to run a momentum strategy and make a decent living at it,” says Agustin Lebron, senior researcher at EquiLibre, a trading firm.
Part of the reason: It takes a while for corporate and other information to spread to various investors, so they slowly build positions, producing buying momentum.
“A huge pension fund can’t flip around its positions in a day,” says Lebron. “Behavioral biases also account for some of the effect, as well—people tend to sell their winners too early and hold losers too long.”
Fans of the strategy point to the human tendency to extrapolate from past results—and chase investment returns—noting that momentum patterns have been evident in markets for decades, even centuries. They also say that some of the worst months for momentum strategies are during longer periods of outperformance.
Some have been doing the trade by buying the strongest investments in a sector while shorting the weakest; others lean in to rising markets or asset classes. Still others use a quantitative approach or turn to banks or others who sell ways to make distinct wagers on momentum as a “tradable factor” or a “thematic basket.”
The fans remain believers. “Any strategy has disappointing periods,” says Antti Ilmanen, global co-head of the portfolio solutions group at AQR Capital Management.
The surge in Moderna and other biotech stocks helped crush the momentum trade. These shares were among the most heavily shorted in recent years, but positive news on a cancer vaccine from Moderna and Merck sent those stocks flying, crushing some quant and other hedge funds. Moderna is up around 150% so far this month.
These traders had an especially rough day on Aug. 19, which Goldman Sachs told its clients was the worst day for “systematic long-short managers” in more than two years. About half of the losses were because of momentum trades, the bank said.
Some traders have begun to short, or bet against, the very stocks that propelled the momentum trade earlier this year. Net short positions in futures tied to the Nasdaq-100 index among speculators recently climbed to some of the highest levels of the past two decades, according to data from the Commodity Futures Trading Commission.
The about-face is a sign of how markets have become more treacherous for investors, even as indexes keep climbing. Part of the issue: the recent meltdown of Situational Awareness, a hedge fund that had piled into some of the most popular momentum shares, including chip stocks. After a period of market tumult, Nvidia shares rocketed almost 9% after its earnings, showing how quickly sentiment can shift.
Some investors say the run-up in share prices driving tech stocks higher reminds them at times of the dot-com frenzy decades ago.
Mike Ogborne, the founder of San Francisco-based Ogborne Capital Management, said he has grown more cautious on technology stocks and is keeping more of his portfolio in cash than he typically does.
And he is nervous about the surge in spending by technology giants and quarterly capital expenditures that keep rising.
“It is a little bit like Cinderella and the clock striking midnight. You don’t know when midnight is going to come around,” Ogborne said. “They don’t send a memo around telling you when the capex cycle is over.”
