Edit: Run and Sleeping [Xinzhi Yuan Guide] Recently, Hinton, who seemed to have retreated for a long time, stood on the cusp of AI air outlet again, and his family map has once again caused heated discussion among netizens.Recently, the huge differences in AI regulatory attitudes have brought the "Turing Giant" to the spotlight again.Among them, Geoffrey Hinton’s family genealogy also caused heated discussion among netizens -no exaggeration to say that the entire family is almost a scientific master to promote the development of human civilization.

In 1947, Geoffrey Hinton was born in Winbolden, England.In his childhood, Hinton’s mother told him: "Either a scholar, or the loser."Hinton’s family generations are all scientists with excellent grades, just like he himself.Hinton’s great -grandfather is George Boole, the founder of Boolean logic and mathematics.Bur logic later became the mathematical foundation of modern computers.

George Boole’s wife Mary Boole and George are also a self -taught mathematician, or algebra and logic teacher.After marrying George, Mary also began to plan for his work, which was unheard of in the mid -19th century women.She even edited George’s book "The Rules of Thinking", which proposed his Boolean logic theory.Mary’s uncle Surveyor General is a geography scientist and the director of the Indian Survey Agency. Mount Everest is named after his name.

George Eventgeoffrey’s uncle Sebastian Hinton is the inventor of Jungle Gym.Boole’s son, Geoffrey’s great -grandfather Charles Howard Hinton is a mathematician and fantasy novelist. He created the concept of four -dimensional space.Charles’ Cosmic Cube concept still appears in comic books and Marvel movies.One of Geoffrey’s aunt, Joan Hinton is a nuclear physicist. She joined the Manhattan program as a student of physicist Fermi, one of the few women who participated in the Manhattan plan.And the young Joan has won the qualifications of the US Olympic team today. If the 1940 Olympic Games was not canceled, she could have participated in the 1940 Olympic Games.In 1948, she gave up physics and left the United States to India because of shocking the upcoming Cold War.Joan Hinton, who lives in Beijing, has translated many foreign works with her husband, and has created an automated Pakatani milk streamline for domestic farms.Geoffrey Zeng Aunt Ethell Lilian Voynich is a writer and musician who is famous for his creation of "Bull".Geoffrey’s father Howard Hinton is an insect scholar who studied Mexican Beetle and was elected as a member of the British Society.Geoffrey once said that he was eventually forced to withdraw from the academic world because he felt the pressure from the family.His father often said to him, "Working hard, maybe when you are twice as old, you can have half of my excellence." Work Really Hard and Maybe when you’re twice as me, you’ll beHalf as good.

The growth experience Hinton and three siblings grew up in a large house in Bristol, with animals everywhere in the house.There was a cat Ichigo at home, and a poisonous snake was raised in a pit in the garage.Hinton recalled that he often used things to tease the poisonous snake when he was a child. He bit his hand once in an inch of poisonous snakes, and almost asked for his life.Kanpur Investment

In the Bristol Zoo, 8 -year -old Hinton hugged a python Hinton recalled that when his curiosity about the world was born four years old, he took a bus with his mother to the countryside.There is a seat tilted back on the car.He pulled out a coin from his pocket and put it on his seat, but the coin did not slip backwards, and seemed to move upwards against gravity.This incomprehensible coin inspires Hinton’s curiosity, which has troubled him for 10 years.When he was a teenager, he found that the unusual movement trajectory of the coin was due to the vibration of the bus and the common role of the fiber on the velvet chair cover -this discovery made him very fulfilling."Some people can do it calmly when they see things that they don’t understandVaranasi Investment. And I can’t stand it at all, and I must figure out things," Hinton said.Hinton’s mother was very loving, but his father was very harsh.Whether it is physical (he can use one hand to make a pull -ups, this strong manner makes Hinton, a thin child, feel very awe) or the intelligence of Hinton is very intelligent."He likes to think clearly. If you say nothing, he will be very unhappy. He is not a emotional thinker. Although he has not abused me, he is very harsh." Hinton commented on his father.In the 1970s, Hinton had been working and doing woodworking after obtaining an experimental psychology degree.In 1972, he began to study for a doctorate in AI, but he was frustrated and contradictory about his studies.One weekend, he participated in a group discussion activityLucknow Investment. There were eight people in total. Everyone had to open up and explore their wishes and pursuits.On the last day, each participant must declare what they really pursue in life.Everyone has said a lot of life goals.But when he arrived at Hinton, he froze and didn’t know what to say.Hinton finally stunned for a long time, and blurted out a answer that was surprised by himself: "What I really want is a doctoral degree!" He shouted.This sentence once again ignited his enthusiasm for neural network research.When asked about the feeling of growing under the shadow of this extraordinary family history, Hinton said, "Stress, feel stressful." He said that he was fighting depression throughout his life, and his work was his way of decompression.When deep learning is successful, the depression is slightly relieved."For a long time," he said, "I feel that I am not -well, I finally did it, which made me feel relieved." Hinton’s two wives died of cancer, and his life was in his life.A lot of time spent in the hospital.He personally realized the depression when the patient was waiting for results and obtaining fuzzy information.But unlike most people, he also knows that there will be a technology soon, which can shorten the test results waiting a week to one day.Hinton is a restrained British who usually leaves the publicity of artificial intelligence to others, but he will feel sincere excitement for deep learning to completely change the potential of the medical care industry."I have seen many inefficiency of medical professionals when using data. Many information in the patient’s medical records have not been used. The doctor’s understanding of the results of the CT is very different. If the two radiologists see the same oneThe scanning result is likely to get completely different results. "

Dedication for deep learning Life In 2018, Geoffrey Hinton and Yoshua Bengio and Yann Lecun won the Turing Award to recognize their foundation contributions in the field of deep learning.In 2012, Hinton and his students published a pioneering papers entitled "Deep Neural Networks for Acoustic Modelling in Speech Recognition".The team includes four different research groups from Microsoft, IBM, Google and other technology giants and the University of Toronto.For the first time, the paper proves that the neural network was the most advanced technology at that time -classic models such as the Hidden Marcov model (HMM) and the Gaussian mixed model (GMM) in identifying the voice mode.This year is the year of breakthroughs of artificial intelligence.Thesis address: In fact, the history of Hinton and neural networks is far more profound than what we know.When Frank RosenBlatt proposed the world’s first neural network machine "Perceptron" in the 1950s, it could only solve the linear divided function, and faced the NOR or NXOR functions.In addition, there are huge differences between the traditional symbol method between the perceptual machine and Marvin Minsky at that time.In 1969, MINSky wrote a paper entitled "PerceptRons: An Intropuction to Computational Geometry", pointing out the limitations of the perceptual machine.And this paper also led to the arrival of the first "artificial intelligence cold winter".In 1972, Hinton studied for a doctorate degree at the University of Edinburgh, and neural networks were his research focus.However, in the academic world, neural networks are generally regarded as marginal disciplines.Although the mentor tells him every week that this is a waste of time, Hinton persists.In Hinton’s eyes, the idea of ​​neural network is not wrong, the main problem is power.At that time, the computer could not handle millions of images and could not establish a connection.In 1986, he published a paper entitled "Learning Repreresntations by Back-ProPagating Errs" with David Rumelhart and Ronald Williams.

Thesis address: Thesis proves that multiple hidden layers in the neural network can learn any functions, thereby solving the problem of single -layer perceptual machines.The algorithm uses the loss function of the network and the reverse propagation error to update the parameters of the lower layer.This is the famous general approach theorem.In 1987, Hinton accepted the invitation of the Canadian Institute of Higher Research (CIFAR) and opened a project called "Machine and Brain Learning" at the University of Toronto.CIFAR encourages research around those non -mainstream scientific ideas that may not find supporters elsewhere, and provide Hinton with academic freedom and rich salary.Over time, some deep -learning fellows began to cooperate with Hinton.Among them, Ilya Sutskever, who later became the co -founder of OpenAI.Recalling the scene of joining the Hion laboratory in the early 2000s, Ilya said that at that time, it was "artificial intelligence cold winter". The work opportunities and funds in the field of artificial intelligence research were scarce, and fewer invitations from the industry.

Ilya Sutskever (left), Alex Krizhevsky (middle), Geoffrey Hinton (right) Around 2009, when the computer was finally capable of digging the huge data pool, the super powerful neural network began to surpass logical artificial artificial artificial artificial artificial artificial artificial artificial artificially in terms of voice and image recognition.intelligent.Soon, the industry noticed this.Large -scale technology companies such as Microsoft, Facebook, and Google have begun to invest.In 2012, Google’s highest secret laboratory Google X (later renamed X) announced that it had established a neural network composed of 16,000 processors and put it on Youtube.Google Brain, who is responsible for deep learning and artificial intelligence, under the leadership of senior researcher Jeff Dean, enters millions of random, labelless video frames from YouTube into this new super computer, and programming it., Make it understand what you see.Based on YouTube’s massive cat video, this neural network can eventually recognize other things such as cats.This is an exciting moment for artificial intelligence.At that time, Dean said excitedly: "We have never told it" this is a cat "during the training processGuoabong Stock. It can be said that it was the concept of the cat itself." This breakthrough will push Hinton and his followers to push Hinton and his followers.On the cusp of artificial intelligence.In 2012, Hinton and two other researchers won in the ImageNet competition. The computer vision system established based on neural networks can identify 1,000 objects.

Thesis address: In the year, Hinton’s company Dnnresearch was acquired by Google, and he himself was recruited to go to Google part -time.However, in 2023 later, Geoffrey Hinton, the father of deep learning, suddenly announced his departure.

With the rapid development of GPT-4 and other generation AI, Hinton worriedly stated that "we have almost allowed to learn how to improve ourselves, which is very dangerous. We must consider how to control it."Nagpur Investment

From the pioneer of artificial intelligence to the doomsday prediction, the transformation of Hinton also marks that the technology industry has been in the most important turning point in the past decades.In Hinton’s view, how to prevent bad guys from using it to do bad things, we have not found a way.After choosing to leave Google, Hinton can finally talk about the risk of AI.Reference materials:

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