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Andrew Yan-Tak Ng (; born April 18, 1976) is a British-American computer scientist and technology entrepreneur focusing on machine learning and artificial intelligence (AI). Ng was a cofounder and head of Google Brain and was the former Chief Scientist at Baidu, building the company's Artificial Intelligence Group into a team of several thousand people.
Ng is an adjunct professor at Stanford University (formerly associate professor and Director of its Stanford AI Lab or SAIL). Ng has also worked in the field of online education, cofounding Coursera and DeepLearning.AI. He has spearheaded many efforts to "democratize deep learning" teaching over 8 million students through his online courses. Ng is renowned globally in computer science, recognized in Time magazine's 100 Most Influential People in 2012 and Fast Company Most Creative People in 2014. His influence extends to being named in the Time100 AI Most Influential People in 2023.
In 2018, he launched and currently heads the AI Fund, initially a $175-million investment fund for backing artificial intelligence startups. He has founded Landing AI, which provides AI-powered SaaS products.
On April 11, 2024, Amazon announced the appointment of Ng to its board of directors.
In 1997, he earned his undergraduate degree with a triple major in computer science, statistics, and economics from Carnegie Mellon University in Pittsburgh, Pennsylvania. Between 1996 and 1998 he also conducted research on reinforcement learning, model selection, and feature selection at the AT&T Bell Labs.
In 1998, Ng earned his master's degree in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology (MIT) in Cambridge, Massachusetts. At MIT, he built the first publicly available, automatically indexed web-search engine for research papers on the web. It was a precursor to CiteSeerX/ResearchIndex, but specialized in machine learning.
In 2002, he received his Doctor of Philosophy (Ph.D.) in Computer Science from the University of California, Berkeley, under the supervision of Michael I. Jordan. His thesis is titled "Shaping and policy search in reinforcement learning" and is well-cited to this day.
He started working as an assistant professor at Stanford University in 2002 and as an associate professor in 2009.
He currently lives in Los Altos Hills, California. In 2014, he married Carol E. Reiley. They have two children: a daughter born in 2019 and a son born in 2021. The MIT Technology Review named Ng and Reiley an "AI power couple".
In 2008, his group at Stanford was one of the first in the US to start advocating the use of GPUs in deep learning. The rationale was that an efficient computation infrastructure could speed up statistical model training by orders of magnitude, ameliorating some of the scaling issues associated with big data. At the time it was a controversial and risky decision, but since then and following Ng's lead, GPUs have become a cornerstone in the field. Since 2017, Ng has been advocating the shift to high-performance computing (HPC) for scaling up deep learning and accelerating progress in the field.
In 2012, along with Stanford computer scientist Daphne Koller he cofounded and was CEO of Coursera, a website that offers free online courses to everyone. It took off with over 100,000 students registered for Ng's popular CS229A course. Today, several million people have enrolled in Coursera courses, making the site one of the leading massive open online courses (MOOCs) in the world.
In 2014, he joined Baidu as chief scientist, and carried out research related to big data and AI. There he set up several research teams for things like facial recognition and Melody, an AI chatbot for Health care. He also developed for the company the AI platform called DuerOS and other technologies that positioned Baidu ahead of Google in the discourse and development of AI.
In March 2017, he announced his resignation from Baidu.He soon afterward launched DeepLearning.AI, an online series of deep learning courses (including the AI for Good Specialization). Then Ng launched Landing AI, which provides AI-powered SaaS products.
In January 2018, Ng unveiled the AI Fund, raising $175 million to invest in new Startup company. In November 2021, Landing AI secured a $57 million round of series A funding led by McRock Capital, to help manufacturers adopt computer vision.
In October 2024, Ng's AI Fund made its first investment in India, backing AI healthcare startup Jivi, which uses AI for diagnoses, treatment recommendations, and administrative tasks. The investment highlights the growth of India's AI sector, expected to reach $22 billion by 2027.
During graduate school, together with David M. Blei and Michael I. Jordan, Ng co-authored the influential paper that introduced latent Dirichlet allocation (LDA) for his thesis on reinforcement learning for drones.David M. Blei, Andrew Y. Ng, Michael I. Jordan. Latent Dirichlet allocation. The Journal of Machine Learning Research, Volume 3, January 3, 2003, which is one of the two papers that independently discovered Latent Dirichlet allocation
His early work includes the Stanford Autonomous Helicopter project, which developed one of the most capable autonomous helicopters in the world. He was the leading scientist and principal investigator on the STAIR (Stanford Artificial Intelligence Robot) project, which resulted in Robot Operating System (ROS), a widely used open source software robotics platform. His vision to build an AI robot and put a robot in every home inspired Scott Hassan to back him and create Willow Garage.
He is also one of the founding team members for the Stanford WordNet project, which uses machine learning to expand the Princeton WordNet database created by Christiane Fellbaum.In 2011, Ng founded the Google Brain project at Google, which developed large-scale artificial using Google's distributed computing infrastructure. Among its notable results was a neural network trained using deep learning algorithms on 16,000 , which learned to recognize cats after watching only YouTube videos, and without ever having been told what a "cat" is. The project's technology is also currently used in the Android operating system's speech recognition system.
The seeds of massive open online courses (MOOCs) go back a few years before the founding of Coursera in 2012. Two themes emphasized in the founding of modern MOOCs were scale and availability.
By 2023, Ng has notably expanded access to AI education, with an estimated 8 million individuals worldwide taking his courses via platforms like DeepLearning.AI and Coursera.
Within Stanford, they include Daphne Koller with her "blended learning experiences" and codesigning a peer-grading system, John Mitchell (Courseware, a Learning Management System), Dan Boneh (using machine learning to sync videos, later teaching cryptography on Coursera), Bernd Girod (ClassX), and others. Outside Stanford, Ng and Thrun credit Sal Khan of Khan Academy as a huge source of inspiration. Ng was also inspired by lynda.com and the design of the forums of Stack Overflow.
Widom, Ng, and others were ardent advocates of Khan-styled tablet recordings, and between 2009 and 2011, several hundred hours of lecture videos recorded by Stanford instructors were recorded and uploaded. Ng tested some of the original designs with a local high school to figure the best practices for recording lessons.
In October 2011, the "applied" version of the Stanford class (CS229a) was hosted on ml-class.org and launched, with over 100,000 students registered for its first edition. The course featured quizzes and graded programming assignments and became one of the first and most successful massive open online courses (MOOCs) created by a Stanford professor.
Two other courses on databases (db-class.org) and AI (ai-class.org) were launched. The ml-class and db-class ran on a platform developed by students, including Frank Chen, Jiquan Ngiam, Chuan-Yu Foo, and Yifan Mai. Word spread through social media and popular press. The three courses were 10 weeks long, and over 40,000 "Statements of Accomplishment" were awarded.
His work subsequently led to his founding of Coursera with Koller in 2012. As of 2019, the two most popular courses on the platform were taught and designed by Ng: "Machine Learning" (#1) and "Neural Networks and Deep Learning" (#2).
He is also a member of the board of directors for drive.ai, which uses AI for and was acquired by Apple in 2019.
Through Landing AI, he also focuses on democratizing AI technology and lowering the barrier for entrance to businesses and developers.
He has corefereed hundreds of AI publications in journals like NeurIPS. He has also been the editor of the Journal of Artificial Intelligence Research (JAIR), Associate Editor for the IEEE Robotics and Automation Society Conference Editorial Board (ICRA), and much more.
He has given invited talks at NASA, Google, Microsoft, Lockheed Martin, the Max Planck Society, Stanford, Princeton, UPenn, Cornell, MIT, UC Berkeley, and dozens of other universities. Outside of the US, he has lectured in Spain, Germany, Israel, China, Korea, and Canada.
He has also written for Harvard Business Review, HuffPost, Slate, Apple News, and Quora Sessions' Twitter. He also writes a weekly digital newsletter called The Batch.
Ng contributed one chapter to Architects of Intelligence: The Truth About AI from the People Building it (2018) by the American futurist Martin Ford.
In a December 2023 Financial Times interview, Ng highlighted concerns regarding the impact of potential regulations on open-source AI, emphasizing how reporting, licensing, and liability risks could unfairly burden smaller firms and stifle innovation. He argued that regulating basic technologies like open-source models could hinder progress without markedly enhancing safety. Ng advocated for carefully designed regulations to prevent obstacles to the development and distribution of beneficial AI technologies.
In a June 2024 interview with the Financial Times, Ng expressed concerns about proposed AI legislation in California that would have required developers to implement safety mechanisms such as a "kill switch" for advanced models. He described the bill as creating "massive liabilities for science-fiction risks" and said it "stokes fear in anyone daring to innovate." Other critics argued the bill would impose burdens on Open source developers and smaller AI companies. The bill was ultimately vetoed by Governor Gavin Newsom in September 2024.
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