Datawhale Share
Editor: Heart of the Machine, Source: Time Magazine
"Their insights, desires and shortcomings will determine the direction of this increasingly influential technology."
Just now, Time magazine released a list of the 100 most influential people in the field of AI in 2023.
In this list, we see many familiar scholars and entrepreneurs.
The "Leaders" section includes OpenAI co-founder Sam Altman, Baidu CEO Robin Li, Google DeepMind CEO and co-founder Demis Hassabis, as well as Musk, Kai-Fu Lee, Andrew Ng, Jen-Hsun Huang, etc.
In the "Thinkers" section, Professor Zeng Yi from the Chinese Academy of Sciences, Professor Li Feifei from Stanford University, Ilya Sutskever, co-founder and chief scientist of OpenAI, and the three giants of deep learning Geoffrey Hinton, Yann LeCun, and Yoshua Bengio were all selected.
Below we have compiled a list of some of the selected candidates. For the complete list, please view: https://time.com/collection/time100-ai/
leader
Sam Altman
Sam Altman is the CEO of OpenAI, and many people call him the father of ChatGPT. In addition, he co-founded Worldcoin in 2020. Previously, he served as president of Y Combinator and briefly as CEO of Reddit.
This year, OpenAI released ChatGPT and GPT-4 large language models, which triggered a craze in training large language models in the AI circle. OpenAI's breakthrough shows that the world's most advanced AI companies have enough supercomputing, data, and funding that they may soon be able to conjure systems with ChatGPT-like capabilities.
It is commendable that in addition to promoting cutting-edge research in AI technology, OpenAI under Altman's leadership pioneered the use of human feedback for reinforcement learning. In June, OpenAI announced that it would invest 20% of its computing power in solving the super-alignment problem to ensure maximum human Benefit.
Demis Hassabis
Demis Hassabis is currently the CEO and co-founder of Google DeepMind and is known as the father of AlphaGo. Research such as AlphaGo, AlphaFold, and DeepMind AlphaStar were all completed under the leadership of Demis. In 2010, Demis founded DeepMind and served as CEO, focusing on research on AGI. In 2014, Google acquired DeepMind for US$400 million. On April 21, 2023, Alphabet stated that it would merge DeepMind and Google Brain to form a new Google DeepMind team, with Demis serving as CEO.
Robin Li
Robin Li is the founder, chairman and CEO of Baidu. In January 2000, Robin Li founded Baidu. In January 2018, Robin Li appeared on the cover of the first issue of Time magazine in 2018 and was dubbed "The Innovator", becoming the first Chinese Internet entrepreneur to appear on the cover of the magazine.
"Times" believes that as one of China's most important scientists, Robin Li invests a large amount of money in technology research and development every year and has been riding the wave of global AI. Baidu has become an industry leader in search engines, driverless driving, virtual voice assistants, and generative AI products.
Elon Musk
Musk is the founder and CEO of Tesla (TESLA), CEO and CTO of Space Exploration Technology Company (SpaceX), CEO of Twitter, founder of Neuralink, etc.
From 1995 to 2002, Musk and his partners founded Zip2 and PayPal; in 2002, he invested US$100 million to establish Space Exploration Technology Company (Space Tesla invested US$6.3 million and served as chairman of Tesla; in 2006, Musk invested US$10 million to found the photovoltaic power generation company Solar City Company; in September 2018, he resigned as chairman of Tesla, but continued to serve as Tesla chairman. CEO of SLA. On March 2, 2021, Hurun Research Institute released the "2021 Hurun Global Rich List", and Musk became the world's richest man for the first time with a wealth of 1.28 trillion yuan. In October, Musk became the first person in history to be worth more than $300 billion, making him the richest person in the history of Forbes. In December, he was named Time's 2021 Person of the Year.
Kai-fu Lee
Kai-Fu Lee is Chairman and CEO of Sinovation Ventures. In 1998, Kai-Fu Lee joined Microsoft and founded and led Microsoft China Research Institute in China. In 2000, he served as Microsoft's global vice president. In 2002, Kai-fu Lee was elected IEEE Fellow. In March this year, Kai-Fu Lee announced the establishment of a new company, Project AI 2.0. After a three-month preparation period, the AI2.0 company incubated under the leadership of Kai-fu Lee personally made its first public appearance, officially announcing the new brand of 01.AI, and the official website (01.AI) was simultaneously launched. In August, Beijing 01.AI Information Technology Co., Ltd. was established.
Andrew Ng
Andrew Ng is an associate professor in the Department of Computer Science and Department of Electrical Engineering and director of the Artificial Intelligence Laboratory at Stanford University. He is one of the most authoritative scholars in the field of artificial intelligence and machine learning. Ng is also the co-founder (with Daphne Koller) of the online education platform Coursera. In 2007, Ng won the Sloan Award; in 2008, Ng was selected into "the MIT Technology Review TR35", which is the 35 technological innovation heroes selected by the "MIT Technology Entrepreneurship" magazine. The selected candidates are 35 people under the age of 35 in the world. One of the top innovators; in 2013, Ng was selected as one of the 100 most influential people in the world by Time magazine, becoming one of the 16 representatives of the technology industry.
Jen-Hsun Huang
Jensen Huang is the founder and CEO of Nvidia. He founded Nvidia in 1993. In 2001, he was selected into Fortune's 40 richest people under 40 years old; in 2020, he was selected into the "2020 Forbes Global Billionaires List". On May 30, 2023, NVIDIA became the first chip company with a market value of US$1 trillion, and the ninth company in history to enter the "Trillion Club" with a US dollar market value.
Alexander Wang
Alexandr Wang became the world's youngest self-made billionaire at the age of 24. He dropped out of MIT five years ago and founded the AI startup Scale AI in 2016. He was only 19 when the company was founded. It's the summer vacation of freshman year. Currently, Scale AI’s customers include technology giants such as Meta, Microsoft and OpenAI.
innovator
Ted Chiang
Jiang Fengnan is one of the best contemporary Chinese science fiction writers. He graduated from the Computer Science Department of Brown University. His short stories have won four Nebula Awards and four Hugo Awards. In February this year, Jiang Fengnan published an article "ChatGPT Is a Blurry JPEG of the Web" in The New Yorker, discussing his views on ChatGPT.
Sougwen Chung
Zhong Sujun is a former researcher at MIT Media Lab, an interdisciplinary artist, and a pioneer in the field of human-computer collaboration. In 2019, she won the "Women of the Year Award 2019", the highest award of the "Monte Carlo Women Award" for her contribution to the fields of art and science.
Zhong Sujun used her own paintings to train the neural network, and added the neural network that learned her own style to the robot DOUG, so that DOUG could paint on the same stage as her. Zhong Sujun is currently developing the fifth generation DOUG robot.
Nancy Xu
Nancy Xu is the founder and CEO of the startup Moonhub. Moonhub aims to use artificial intelligence to connect businesses with top talent and make the recruitment process fairer. Moonhub was established in June 2022, and so far more than 100 companies around the world have used Moonhub's services.
Thinker
Geoffrey Hinton
Geoffrey Hinton was born in 1947 in Wimbledon, England, after World War II. In 1978, Hinton received a PhD in artificial intelligence from Edinburgh. After teaching at Carnegie Mellon University for five years, he became a fellow at the Canadian Institute for Advanced Study and joined the faculty of the Department of Computer Science at the University of Toronto, where he is now an Emeritus Professor.
In 2012, a research team led by Geoffrey Hinton in Toronto achieved a major breakthrough in deep learning that revolutionized speech recognition and object classification. The convolutional neural network "Alexnet" he designed in collaboration with students Alex Krizhevsk and Ilya Sutskever won the ImageNet 2012 Challenge with a result far exceeding the second place, reducing the visual recognition error rate on the ImageNet data set to 15.3%, only Half of what it was before. This became a milestone in the field of computer vision.
After this, Hinton and two students began receiving generous compensation from large technology companies. They set up a shell company called DNN-research to auction off their expertise, and four technology companies - Google, Microsoft, Baidu and DeepMind - competed to acquire the company for tens of millions of dollars. A week later, Hinton chose Google. In 2013, he joined Google Brain. Ten years later, in May of this year, Hinton announced his departure from here.
Hinton has said that if there is any hope, it lies in the next generation, noting that he is too old to continue to contribute to AI research. Many scientists turn to policy-based jobs later in their careers, but he turned down an offer to take such a role at Google. "I've never been good at or interested in policy issues," he told Time magazine. "I'm a scientist."
Li Feifei
Li Feifei is a professor of computer science at Stanford University, an academician of the National Academy of Engineering, and an academician of the National Academy of Medicine. Her areas of expertise are computer vision and cognitive neuroscience.
In addition to her work at Google, Li Feifei has spent her career in academia. In 2016, Li Feifei joined the Google Cloud artificial intelligence and machine learning China center team and served as one of the team leaders as the chief scientist of Google Cloud. In September 2018, she announced her return to teach at Stanford University and continues to participate in Stanford University's AI research.
Feifei Li's work includes cognitively inspired AI, machine learning, deep learning, computer vision and AI + healthcare, especially ambient intelligence systems for healthcare delivery. She also works in cognitive and computational neuroscience. She invented ImageNet and the ImageNet Challenge, an important large-scale data set and benchmarking effort.
Zeng Yi
Zeng Yi is currently a researcher at the Institute of Automation, Chinese Academy of Sciences, and a member of the advisory board of the Institute of Artificial Intelligence Ethics at the University of Oxford. His research fields include brain-inspired artificial intelligence, artificial intelligence philosophy and ethics. As a member of the World Health Organization Expert Group on the Ethics and Governance of Artificial Intelligence in Health and Health, he participated in the entire process of compiling and publishing the report "World Health Organization Guidelines on the Ethics and Governance of Artificial Intelligence in Health and Health".
Yann LeCun
After Yann LeCun was a French computer scientist who hypothesized in the 1980s that artificial neural networks could mimic the human brain, his idea was widely derided as fantasy for decades. But thanks to technological breakthroughs in the field, LeCun's ideas laid the foundation for the current generative AI revolution.
Today, LeCun is Meta's chief artificial intelligence scientist, and he's still making bold, controversial statements and arguing with everyone he disagrees with.
Yann LeCun expressed his views on ChatGPT: "As far as the underlying technology is concerned, ChatGPT has no special innovation, nor is it anything revolutionary. Many research laboratories are using the same technology and carrying out the same work."
For another example, Yann LeCun disagrees with the term "general artificial intelligence". He believes that there is no so-called "general" intelligence at all. Human intelligence is not general intelligence, but is only good at certain tasks. The goal of mankind should be to create human beings. Human-level Al.
"I could stay silent, but that's not my style," LeCun said in a video interview with TIME.
Joshua Bengio
Yoshua Bengio was born in Paris, France, and studied computer engineering at McGill University. From 1986 to 1991, he continued to study "computer science" until he graduated with a Ph.D., and then worked as a postdoctoral researcher at the Massachusetts Institute of Technology for a period of time. In 1992, he went to the LeCun group of AT&T Bell Labs in the United States to do learning and vision algorithm research. Since 1993, he has been a full professor at the University of Montreal, responsible for computer science and operations research. He is also the founder and scientific director of MILA.
In 2003, Bengio laid the foundation for modern large-scale language models by demonstrating that neural networks can learn human language patterns by predicting the next word (e.g., autocorrect). In 2014, Bengio collaborated with Ian Goodfellow to propose a method of training AI, allowing two AIs to compete with each other, with one generating content and the other judging its quality.
Stuart Russell
Stuart Russell works at the University of California, Berkeley, where he is currently a professor in the Department of Computer Science (former chair of the department) and director of the Center for Human-Compatible Artificial Intelligence. He received the National Science Foundation Presidential Award for Outstanding Young Scientists in 1990 and the IJCAI Computing and Ideas Award in 1995. He is a Fellow of AAAI, ACM and AAAS and has published more than 300 papers in the field of artificial intelligence, covering a wide range of topics.
Together with Peter Norvig, he authored the authoritative book Artificial Intelligence: A Modern Approach, which has been used by 1,547 colleges and universities in 134 countries.
Regarding the popular ChatGPT, Professor Russell believes that the key is to distinguish the task domain and figure out under what circumstances it is used: ChatGPT can be a good tool if it can be anchored on the basis of facts and combined with the planning system , will bring greater value. But the problem is that we currently don't know how ChatGPT works, and we probably won't be able to figure it out. This will require some conceptual breakthroughs, and such breakthroughs are difficult to predict.
