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Geoffrey Hinton is a British‑Canadian computer scientist and cognitive psychologist known for pioneering artificial neural networks and deep learning. A professor at the University of Toronto, he shared the 2024 Nobel Prize in Physics for foundational work enabling modern machine learning.

[This interview was edited for length and clarity.]

How would you describe the current state of American science?

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I would say it is in a dire state because Trump is doing everything he can to undermine it.

America is still very good at innovation, but as it loses more and more of its leading scientists, it’s getting worse. The source of really revolutionary innovations is typically graduate students working in a well-informed group at a leading university, and that is exactly what the Trump government is undercutting by making it much harder and less attractive for foreign graduate students to come here and attacking the leading universities.

What needs to change in American science?

They need to stop attacking the major universities. They need to stop preventing scientists from other countries coming and working in the U.S. A lot of the U.S. advantage in science and technology has been because of immigrant scientists. They need to restore all the grants that they’ve cut off after [those grants] were awarded. And they need to stop, for political reasons, espousing views that are known to be wrong on things such as climate change, vaccines and the role of basic science. So all of the advances we’ve had, all of the major advances in our civilization, are to do with scientific advances, which only happen when you have institutions that protect scientific freedom and you get the best scientists.

What gives you optimism right now?

The midterms.

What’s your best advice for an early-career scientist?

That depends on whether they’re an American citizen. If they’re not an American citizen, I would advise them to be very cautious about working in the U.S.

How has your field changed in the past few years?

Artificial intelligence has changed a whole lot in the past few years because people have started really becoming aware of the extraordinary progress and the extraordinary risks that go with it. A good example is what happened when Anthropic made it public that it’s developed a coding agent that is very good at finding major flaws in all of the major operating systems. And that’s just the tip of the iceberg. We can expect a lot more things like that over the next few years.