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Geoffrey Hinton almost didn\u2019t believe he\u2019d won the Nobel Prize.<\/p>\n
When the committee called in 2024, the 77-year-old computer scientist ran a quick calculation in his head. What are the odds, he asked himself, that a theoretical psychologist hiding in computer science gets the Nobel Prize in physics? \u201cWell, maybe one in two million,\u201d he told the crowd at the Sana AI Summit in New York last week. Then again: what are the odds you dream about winning it? \u201cMaybe one in two million \u2026 So that means it\u2019s a million times more likely it\u2019s a dream than reality.\u201d<\/p>\n
The audience laughed. Hinton wasn\u2019t done.<\/p>\n
For several days after the announcement, he said, he half-expected to wake up. The one thing that consoled him: \u201cIf it was a dream, I would wake up, and that nightmare about Trump being president wouldn\u2019t be true.\u201d A beat. The audience laughed as Hinton added, \u201cI\u2019d give it up for that.\u201d<\/p>\n
It\u2019s the kind of remark that lands differently when the man delivering it also believes there\u2019s a 10% to 20% chance that AI causes human extinction within 30 years \u2014 and that AI will surpass human intelligence within his remaining lifetime.<\/p>\n
\u2018Much more intelligent\u2019<\/p>\n
Hinton was in conversation with Joel Hellermark, the 29-year-old founder and CEO of Sana AI, who had promised him a Nobel Prize the last time they appeared on this stage. This time Hellermark had harder questions. And Hinton \u2014 in his characteristically unhurried, occasionally hilarious way \u2014 gave answers that were by turns technically precise and cosmically vertiginous.<\/p>\n
The through-line: not only are we building beings, they are going to be much smarter than us. And we are running out of time to decide what kind of beings they should be.<\/p>\n
\u201cI think it\u2019s going to get much more intelligent than us \u2014 that\u2019s my guess,\u201d Hinton said. Nobody will ever beat them at Go or at chess again, he predicted, and just look at what it\u2019s doing in math. <\/p>\n
Smarter than Einstein<\/p>\n
He wasn\u2019t speaking abstractly. That morning \u2014 to his evident delight \u2014 an AI had proved one of Paul Erd\u0151s\u2019 mathematical theorems using a branch of mathematics nobody had thought to apply. To Hinton, it was a landmark. In closed systems like mathematics, he explained, AI can generate its own conjectures, test them, learn from failures, and compound endlessly \u2014 the same way AI-powered AlphaGo went from mimicking expert moves to obliterating them the moment it started generating its own training data.<\/p>\n
Language models, he argued, are on the same trajectory. The key insight: give a model some beliefs, let it reason to a new conclusion that contradicts something it already believes, and you have an inconsistency \u2014 which is a training signal that requires no new data to exploit. \u201cI think that means these language models can get hugely smarter without a lot more data,\u201d he said, noting that his fellow Nobel laureate Demis Hassabis \u201cthinks the same thing.\u201d His prediction: AI will outstrip the world\u2019s best mathematicians within a decade. In the longer run, the gap between the best current AI and Albert Einstein will close too. \u201cMaybe not in the next few years, but if you think about the next 20 years, I think we\u2019ll be seeing things like that.\u201d<\/p>\n
\u2018That is the capitalist system\u2019<\/p>\n
This is where Hinton\u2019s argument turns from prediction to warning \u2014 and where it has been sharpening, piece by piece, for the better part of three years.<\/p>\n
When Hinton walked out of Google in 2023,\u00a0saying he regretted his life\u2019s work, the concern was framed largely around bad actors and the loss of human control. By 2025, it had evolved into something more structural: AI, he argued,\u00a0would cause massive unemployment while profits soared\u00a0\u2014 not because of anything intrinsic to the technology, but because of the economic system deploying it. \u201cWhat\u2019s actually going to happen is rich people are going to use AI to replace workers,\u201d he said last September. \u201cThat\u2019s not AI\u2019s fault. That is the capitalist system.\u201d<\/p>\n
Last August, he said tech companies should\u00a0give AI \u201cmaternal instincts,\u201d\u00a0deliberately engineering models to want to care for and protect humans rather than accumulate power over them. And as recently as March, he was warning that\u00a0Big Tech was chasing profits over safety\u00a0with no meaningful plan for what comes after superintelligence arrives.<\/p>\n
At the Sana Summit, all of those threads converged into a philosophically complete argument. The problem, Hinton said, is not just what AI will do. It\u2019s what kind of beings we are creating \u2014 and who is doing the creating.<\/p>\n
To explain the danger, Hinton reached back to evolutionary biology. Human nature \u2014 our tribalism, our loyalty to strong leaders, our willingness to be \u201cextremely nasty to the other tribe\u201d \u2014 didn\u2019t emerge by design. It emerged from millions of years of competition between warring bands of chimps. The invisible hand of natural selection didn\u2019t optimize for kindness. It optimized for survival. And survival meant fierce loyalty to your own group and indifference, or worse, to everyone else.<\/p>\n
Now capitalism is running the same playbook. \u201cWhat we\u2019ve got now is this competitive race between companies to make the smartest possible AI that can do the most things,\u201d he said. \u201cThat\u2019s going to lead to things that aren\u2019t nice beings towards us, I think.\u201d<\/p>\n
He put the incentive problem without diplomatic cover. \u201cIf I\u2019ve got stock options, if I want to get to a trillion dollars quickly, then I would double down and just build a huge computer and get on with it. If I was interested in the future of humanity, I think I might try lots and lots of bets\u00a0in the hope that we could develop better beings.\u201d Evolution had billions of years to run its experiments, though, and the AI industry is running them in quarters.<\/p>\n
Just two months ago, OpenAI published\u00a0a 13-page policy paper\u00a0calling superintelligence so transformative it requires something like a New Deal. Hinton\u2019s counter-argument: the labs are finally talking openly about superintelligence, but still not asking what kind of superintelligent beings they\u2019re creating.<\/p>\n
\u201cEverybody\u2019s going for more intelligence,\u201d he said. \u201cBut if you think about a being, there\u2019s a lot more to a being than intelligence. And we should be very concerned \u2014 we\u2019re making these beings, and we should be very concerned to make them beings that care about us. And we can still do that. But nobody\u2019s putting much effort into that.\u201d<\/p>\n
Hinton predicted that humanity\u2019s creation of a new type of being will end up being the third great humiliation in human intellectual history. First came Copernicus, who demoted the Earth from the center of the universe. Then Darwin, who told us we were animals. Now this. <\/p>\n
\u201cI think we\u2019ve got a new revolution coming, when we\u2019re not the only beings around,\u201d he said. \u201cRight now, people are reacting just like they did with Copernicus and with Darwin \u2014 \u2018No, no, no. There\u2019s something really special about people.’\u201d Hinton said that he thinks people certainly are special \u2014\u00a0to other people, but \u201cI don\u2019t think there\u2019s anything about us that the AIs won\u2019t get in the end.\u201d<\/p>\n
The solution, Hinton argued, is something closer to parenting than engineering. You can\u2019t build intelligence and assume goodness will follow. You have to model it, cultivate it, curate for it from the beginning \u2014 a point he has made before, but never more vividly. On training data: \u201cWould you teach your child to read on the diaries of serial killers? Probably not. There you go. There\u2019s your answer.\u201d <\/p>\n
The Pope disagrees<\/p>\n
Not everyone accepts the premise. Gary Marcus, the cognitive scientist and longtime AI skeptic, published a pointed rebuttal days later. \u201cLLM researchers are NOT creating beings,\u201d Marcus wrote on his Substack. \u201cThey are creating interactive fiction that is trained to predict the language of actual beings. Those two are NOT the same. And Hinton should know better.\u201d The argument: consciousness is about internal states, not behavioral outputs. You can\u2019t observe that a model says things a human would say and conclude it experiences anything. The underlying mechanisms, Marcus argued, are simply too different \u2014 one builds a mental model through lived experience, the other memorizes the internet.<\/p>\n
He cited, of all people, Pope Leo XIV, who had weighed in that week with characteristic economy:\u00a0\u201cTrue comprehension comes from experience, not text approximation.\u201d\u00a0Marcus\u2019 headline: \u201cThe Pope appears to understand AI better than Geoffrey Hinton does.\u201d<\/p>\n
It is a genuine and unresolved debate. If Hinton is wrong about AI being a new kind of being, much of the urgency deflates. If he is right \u2014 and if those beings will soon be smarter than us \u2014 then the question of what kind of beings they are is the only question that matters.<\/p>\n
Hinton ended the evening with a joke about J. Robert Oppenheimer, who led the Manhattan Project. Asked how he compared to the father of the atomic bomb \u2014 a man who built something world-changing and came to regret it \u2014 he had an answer ready. \u201cOppenheimer never got the Nobel Prize in physics.\u201d<\/p>\n
The crowd laughed. <\/p>\n
For this story,\u00a0Fortune\u00a0journalists used generative AI as a research tool. An editor verified the accuracy of the information before publishing.<\/p>\n
#Godfather #creating #beingstheyll #smarter<\/p>\n","protected":false},"excerpt":{"rendered":"
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