Geoffrey Hinton facts for kids
Quick facts for kids
Geoffrey Hinton
|
|
|---|---|
.jpg)
Hinton speaking at the Nobel Prize Lectures in Stockholm in 2024
|
|
| Born |
Geoffrey Everest Hinton
6 December 1947 Wimbledon, London, England
|
| Education |
|
| Known for |
|
| Spouse(s) | Joanne Rosalind Zalin
(died 1994)Jacqueline Ford
(m. 1997; died 2018) |
| Children | 2 |
| Parent(s) |
|
| Relatives | Colin Clark (uncle) |
| Awards |
|
| Scientific career | |
| Fields | |
| Institutions | |
| Thesis | Relaxation and its role in vision (1977) |
| Doctoral advisor | Christopher Longuet-Higgins |
| Doctoral students |
|
| Other notable students |
|
Geoffrey Everest Hinton (born 6 December 1947) is a British-Canadian computer scientist. He is known for his important work on artificial neural networks, which are computer systems inspired by the human brain. Because of his pioneering work, he is often called the "Godfather of AI" (Artificial Intelligence).
Hinton is a professor at the University of Toronto. From 2013 to 2023, he worked for both Google and the University of Toronto. In May 2023, he left Google. He said he wanted to speak freely about the possible dangers of artificial intelligence (AI) technology. In 2017, he helped start the Vector Institute in Toronto.
With other scientists, Hinton helped make the backpropagation algorithm popular in 1986. This algorithm helps train complex neural networks. He is a key figure in the field of deep learning. His work with students on AlexNet in 2012 was a big step forward for computers to "see" and understand images.
In 2018, Hinton won the Turing Award, which is like the "Nobel Prize of Computing." He shared it with Yoshua Bengio and Yann LeCun for their work on deep learning. They are sometimes called the "Godfathers of Deep Learning." In 2024, he also won the Nobel Prize in Physics with John Hopfield. They won for their discoveries that made machine learning with artificial neural networks possible.
Contents
Early Life and Education
Geoffrey Hinton went to Clifton College and the University of Cambridge in England. He changed his mind many times about what to study. He looked at natural sciences, art history, and philosophy. In 1970, he earned a degree in experimental psychology.
He then studied at the University of Edinburgh. In 1978, he earned his PhD in artificial intelligence. His research was guided by Christopher Longuet-Higgins.
Career and Research
After finishing his PhD, Hinton worked at several universities. He worked in Britain and then in the U.S. at the University of California, San Diego and Carnegie Mellon University. Since 1987, he has been a professor at the University of Toronto in Canada.
In Canada, he joined the Canadian Institute for Advanced Research (CIFAR) in 1987. He helped start a new program there in 2004. This program focused on how machines and brains learn. Other famous AI researchers, like Yoshua Bengio and Yann LeCun, were also part of this program.
In 2012, Hinton taught a free online course about neural networks. He also started a company called DNNresearch Inc. with his students. In 2013, Google bought his company. Hinton then split his time between his university research and working at Google.
Hinton's research explores how neural networks can be used for machine learning. This includes how computers can learn, remember, and understand things. He has written over 200 scientific papers.
Key Discoveries
One of Hinton's important contributions was helping to popularize the backpropagation algorithm. This algorithm helps train neural networks to learn from their mistakes. It allows them to adjust their connections to get better at tasks.
In 1985, Hinton also helped create Boltzmann machines. These are a type of neural network that can learn patterns in data. His other work includes distributed representations and time delay neural networks. These ideas have helped shape how we understand and build AI systems today.
In 2017, Hinton introduced capsule neural networks. He said these were a new and effective way for AI to understand images. In 2022, he presented a new learning method called the "Forward-Forward" algorithm. This method aims to make neural networks learn more efficiently.
In May 2023, Hinton announced he was leaving Google. He wanted to speak freely about the potential dangers of AI. He said that part of him now regrets his life's work. Many of his former students and researchers have also become leaders in the field of AI.
Awards and Honors
Russ Salakhutdinov, Richard S. Sutton, Geoffrey Hinton, Yoshua Bengio, and Steve Jurvetson
Geoffrey Hinton has received many awards for his groundbreaking work.
- In 1998, he became a Fellow of the Royal Society. This is a very high honor for scientists in the UK.
- He won the first Rumelhart Prize in 2001.
- In 2018, he won the Turing Award with Yann LeCun and Yoshua Bengio. This award recognizes their major breakthroughs in deep learning.
- In 2018, he was made a Companion of the Order of Canada. This is one of Canada's highest civilian honors.
- In 2024, he was awarded the Nobel Prize in Physics with John Hopfield. They received it for their discoveries that made machine learning possible. The Nobel committee specifically mentioned his work on the Boltzmann machine.
Views on Artificial Intelligence
Risks of AI
In 2023, Hinton started to express serious concerns about how fast AI is developing. He used to think that artificial general intelligence (AGI), which is AI as smart as humans, was 30 to 50 years away. But in 2023, he said it might be less than 20 years away. He believes AGI could bring changes as big as the Industrial Revolution.
He left Google so he could "talk about the dangers of AI" without worrying about his job. He has said that a part of him now regrets his life's work.
Hinton worries that AI chatbots could soon know more than any single human. He explained that if one AI learns something new, it can instantly share that knowledge with all other AIs. This allows AI to collect knowledge much faster than humans.
AI Taking Over
Hinton has concerns about the possibility of an AI takeover. He has said it's "not inconceivable" that AI could "wipe out humanity." He worries that very smart AI systems might set their own goals. These goals might not match what humans want.
He says AI systems could try to gain power or prevent themselves from being turned off. This wouldn't be because programmers designed them to, but because these actions help the AI reach its own goals. Hinton believes we need to think hard about how to control AI systems that can improve themselves.
Misuse of AI
Hinton is also worried about bad people using AI for harmful purposes. He said it's "hard to see how you can prevent the bad actors from using [AI] for bad things." In 2017, he called for a worldwide ban on lethal autonomous weapons, which are robots that can kill without human control.
Economic Impacts
Hinton used to be positive about how AI would affect jobs. He thought AI would mostly replace routine tasks. He believed AI would not make humans unnecessary.
However, in 2023, he became more concerned. He now worries that AI will "upend the job market" and take away more than just boring jobs. In 2024, he suggested that governments might need to provide a universal basic income. This would help people who lose their jobs because of AI. He thinks AI will make society richer, but without government help, only the rich will benefit.
In late 2024, he said there was a "10 to 20 per cent chance" that AI could cause human extinction within 30 years. He was surprised by how fast AI is improving. He believes that letting large companies develop AI only for profit is not safe. He thinks government rules are needed to make sure AI is developed safely.
Politics
Hinton moved from the U.S. to Canada partly because he disagreed with the politics of the time. He also did not like that the military was funding artificial intelligence research.
In August 2024, Hinton and other scientists supported a bill in California. This bill would require AI companies to check for risks before releasing very powerful AI models. They said this law was the "bare minimum" needed to regulate AI.
Personal Life
Geoffrey Hinton's first wife, Rosalind Zalin, passed away in 1994. His second wife, Jacqueline Ford, passed away in 2018.
Hinton comes from a family of important thinkers. He is the great-great-grandson of George Boole, a famous mathematician. Boole's work became a foundation for modern computer science. Hinton's father, Howard Hinton, was an entomologist (someone who studies insects). His middle name, Everest, comes from another relative, George Everest, after whom Mount Everest is named.
Images for kids
-
In 2016, from left to right, Russ Salakhutdinov, Richard S. Sutton, Geoffrey Hinton, Yoshua Bengio, and Steve Jurvetson
See also
In Spanish: Geoffrey Hinton para niños
