Geoffrey Hinton Biography
Geoffrey Hinton is a British-Canadian cognitive psychologist and computer scientist best recognized for his research on artificial neural networks. From 2013 until 2023, he worked at Google Brain and the University of Toronto, before departing in May 2023 due to AI technology risks. In 2017, Hinton co-founded and became chief scientific advisor of the Vector Institute in Toronto.
How old is Geoffrey Hinton? – Age
He is 75 years old as of 6 December 2023. He was born in 1947 in Wimbledon, London, United Kingdom. His real name is Geoffrey Everest Hinton.
Geoffrey Hinton Family
Hinton is the great-great-grandson of mathematician and educator Mary Everest Boole and her husband, logician George Boole, whose work helped lay the groundwork for modern computer science. Another of his great-great-grandfathers was surgeon and author James Hinton, the father of mathematician Charles Howard Hinton. Howard Hinton, an entomologist, was Hinton’s father. His middle name is derived from another cousin, Surveyor General of India George Everest, after whom the peak is called. Colin Clark, the economist, is his uncle.
Geoffrey Hinton Education
Hinton attended King’s College, Cambridge. He eventually graduated in 1970 with a bachelor of arts in experimental psychology after changing his major several times between natural sciences, history of art, and philosophy. He continued his education at the University of Edinburgh, where he received a Ph.D. in artificial intelligence in 1978 for research directed by Christopher Longuet-Higgins.
Geoffrey Hinton Wife
Rosalind Zalin, Hinton’s first wife, died of ovarian cancer in 1994. Jackie, his second wife, died of cancer in April 2023.
What is the net worth of Geoffrey Hinton? – Net Worth
He has an estimated net worth of $10 million.
Why did Geoffrey Hinton leave Google? – Google
Hinton announced his retirement from Google in an interview with The New York Times published on May 1, 2023, so that he could “talk about the dangers of AI without considering how this impacts Google.” He admitted that “a part of him now regrets his life’s work” as a result of his misgivings, and he expressed concern about a race between Google and Microsoft.
Geoffrey Hinton Artificial Intelligence
Hinton voiced concerns about the quick growth of artificial general intelligence (AGI) around 2023. Hinton previously felt that AGI was “30 to 50 years or even longer away.” In a March 2023 interview with CBS, he suggested that “general-purpose AI” may be less than 20 years away and might bring about changes “comparable in scale to the Industrial Revolution or electricity.”
Hinton announced his retirement from Google in an interview with The New York Times published on May 1, 2023, so that he could “talk about the dangers of AI without considering how this impacts Google.” He admitted that “a part of him now regrets his life’s work” as a result of his misgivings, and he expressed concern about a race between Google and Microsoft.
Hinton revealed in an interview with the BBC in early May 2023 that AI may soon surpass the information capacity of the human brain. Some of the threats posed by these chatbots were termed as “quite scary” by him. Hinton argued that chatbots can learn on their own and share their expertise. This means that any new knowledge acquired by one copy is automatically distributed to the entire group. This enables AI chatbots to collect knowledge far beyond the capacity of any individual.
Geoffrey Hinton Career
Hinton worked at the College of Sussex and (after trouble tracking down subsidizing in England), the College of California, San Diego and Carnegie Mellon College. He was the establishing overseer of the Gatsby Magnanimous Establishment Computational Neuroscience Unit at College School London and is right now a teacher in the software engineering division at the College of Toronto. He holds a Canada Exploration Seat in AI and is currently[when?] a consultant for the Learning in Machines and Minds program at the Canadian Establishment for Cutting edge Exploration. Hinton showed a free web-based seminar on Brain Organizations on the training stage Coursera in 2012. He joined Google in Walk 2013 when his organization, DNNresearch Inc., was obtained, and was around then wanting to “split his time between his college examination and his work at Google”.
Hinton’s exploration concerns approaches to involving brain networks for AI, memory, insight, and image handling. He has composed or co-composed in excess of 200 friend assessed distributions. At the Gathering on Brain Data Handling Frameworks (NeurIPS) he presented another learning calculation for brain networks that he calls the “Forward” calculation. The possibility of the new calculation is to supplant the customary forward-in reverse passes of backpropagation with two forward passes, one with positive (for example genuine) information and the other with negative information that could be produced exclusively by the organization.
While Hinton was a postdoc at UC San Diego, David E. Rumelhart and Hinton and Ronald J. Williams applied the backpropagation calculation to multi-facet brain organizations. Their trials demonstrated the way that such organizations can learn helpful inside portrayals of information. In a meeting of 2018, that’s what hinton said “David E. Rumelhart thought of the essential thought of backpropagation, so it’s his creation”. Albeit this work was significant in advocating backpropagation, recommending the approach was not the first. Switch mode programmed separation, of which backpropagation is an extraordinary case, was proposed by Seppo Linnainmaa in 1970, and Paul Werbos proposed to utilize it to prepare brain networks in 1974.
During a similar period, Hinton co-imagined Boltzmann machines with David Ackley and Terry Sejnowski. His different commitments to brain network research incorporate dispersed portrayals, time defer brain organization, combinations of specialists, Helmholtz machines and Result of Specialists. In 2007, Hinton coauthored a solo learning paper named Unaided learning of picture changes. An open prologue to Geoffrey Hinton’s exploration can be found in his articles in Logical American in September 1992 and October 1993.
In October and November 2017 separately, Hinton distributed two open access research papers on the subject of container brain networks,[44][45] which as per Hinton, are “at long last something that functions admirably”.
In May 2023, Hinton freely reported his abdication from Google. He made sense of his choice by saying that he needed to “uninhibitedly take a stand in opposition to the dangers of A.I.” and added that a piece of him presently laments his all consuming purpose.
Remarkable previous PhD understudies and postdoctoral specialists from his gathering incorporate Peter Dayan, Sam Roweis, Max Welling, Richard Zemel, Brendan Frey, Radford M. Neal, Yee Whye Teh, Ruslan Salakhutdinov, Ilya Sutskever, Yann LeCun, Alex Graves, and Zoubin Ghahramani.