Andrew Ng

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Andrew Ng
BornAndrew Yan-Tak Ng
4/18/1976
BirthplaceLondon, England, United Kingdom
NationalityBritish-American
OccupationComputer scientist, AI researcher, entrepreneur
EmployerStanford University; DeepLearning.AI; AI Fund; Landing AI
Known forDeep learning; Coursera; Google Brain; Baidu AI Group; DeepLearning.AI
EducationCarnegie Mellon University (B.S.)
Massachusetts Institute of Technology (M.S.)
University of California, Berkeley (Ph.D.)
Spouse(s)Carol Reiley
Websiteandrewng.org

Andrew Yan-Tak Ng (born April 18, 1976) is a British-American computer scientist and artificial intelligence researcher whose work across academia, industry, and education has substantially shaped the development of modern machine learning and deep learning. Raised across multiple countries before settling in the United States, he developed an early interest in mathematics and computing that carried him from Carnegie Mellon University through graduate study at MIT and UC Berkeley, and into leadership roles at some of the world's most influential technology organizations. He co-founded Coursera, now one of the world's largest online education platforms, and co-founded Google Brain, Google's deep learning research project. He later served as Chief Scientist at Baidu, overseeing major expansions in the company's artificial intelligence capabilities. Since 2017, his primary focus has been DeepLearning.AI, an educational technology company, and AI Fund, a venture studio he founded to build AI-driven companies across multiple industries.

Early life

Andrew Yan-Tak Ng was born on April 18, 1976, in London to parents of Hong Kong origin. His family moved frequently during his childhood, and he spent significant time in both Hong Kong and Singapore before coming to the United States for his undergraduate studies.[1] That international upbringing exposed him to different educational systems and cultures, an experience that would inform his later advocacy for global access to education. His father was a physician, and the family placed a strong emphasis on academic achievement. That environment helped direct Ng's interest toward science and mathematics, and by the time he began university, he had focused his attention on computer science — specifically on theoretical questions about how machines could be made to learn from data rather than follow explicitly programmed instructions.

Education

Ng completed his undergraduate degree in computer science at Carnegie Mellon University in Pittsburgh, Pennsylvania.[2] He then earned a Master of Science in computer science from the Massachusetts Institute of Technology. His doctorate came from the University of California, Berkeley, where his dissertation focused on reinforcement learning and probabilistic approaches to machine learning, work conducted under the supervision of Michael I. Jordan.[3] That graduate training placed him at the crossroads of statistics, optimization theory, and computational modeling — areas that would define his subsequent research agenda. After completing his doctorate, Ng joined Stanford University's faculty, beginning what would become a highly productive period in his professional life.

Career

Stanford University

At Stanford's Department of Computer Science, Ng became an associate professor and established the Stanford Artificial Intelligence Laboratory (SAIL). His research explored how deep learning could be applied to problems in computer vision, natural language processing, and robotics.[4] His group demonstrated that unsupervised learning with large neural networks could produce useful internal representations of data when trained on large, varied datasets — work that contributed to the conceptual groundwork for what later became widely known as the deep learning revolution.

Alongside his research, Ng developed a reputation as an unusually effective teacher. His machine learning course at Stanford, designated CS229, drew consistently high enrollments and was widely regarded by students as one of the clearest introductions to the subject available. In 2011, he made the decision to offer the course online to the general public. That decision attracted an enrollment of over 100,000 students and directly preceded the founding of Coursera.[5]

Coursera

In 2012, Ng co-founded Coursera with fellow Stanford computer science professor Daphne Koller.[6] The platform was built around massive open online courses (MOOCs), which allow learners anywhere with internet access to receive university-level instruction at low or no cost. Within its first year, Coursera had enrolled millions of students and had partnered with dozens of major universities across the United States and internationally. The platform has since grown into one of the world's most widely used online education services, offering not only individual courses but full degree programs through accredited universities, with over 100 million registered learners. Ng served as co-chairman and remained a vocal advocate for the platform's educational mission following his departure from day-to-day operations.[7]

Google Brain

In 2011, while still at Stanford, Ng co-founded Google Brain at Google with Jeff Dean and Greg Corrado.[8] The project's central question was whether very large neural networks, trained on massive amounts of unlabeled data using Google's computing infrastructure, could learn meaningful representations without any human supervision. The answer emerged from one landmark experiment: a neural network trained on millions of frames drawn from YouTube videos spontaneously developed an internal representation of a cat without having been told what a cat was. The result attracted substantial media attention and accelerated academic and industrial interest in deep learning.[9] Google Brain subsequently grew into one of the most prominent AI research organizations in the technology industry. In 2023, Google Brain merged with DeepMind to form Google DeepMind.

Baidu

In 2014, Ng joined Baidu, the Chinese technology company, as Chief Scientist, based at their Silicon Valley AI laboratory in Sunnyvale, California.[10] In that role, he oversaw AI research teams in both the United States and China, directing the integration of deep learning into Baidu's core products, including search, voice recognition, and autonomous driving systems. Under his scientific leadership, Baidu's AI division grew substantially and published influential research in speech recognition and computer vision. He departed in March 2017, citing a desire to pursue independent projects.[11]

AI Fund and DeepLearning.AI

After leaving Baidu, Ng founded AI Fund, a venture studio that builds AI-driven companies across multiple industries. Rather than investing in existing startups, AI Fund identifies high-potential AI applications and constructs new companies around them from the ground up.[12]

He also launched DeepLearning.AI in 2017, an educational technology company providing structured AI education through online courses and specializations. The company's courses, distributed primarily through Coursera, have reached millions of learners globally and cover topics ranging from neural network mathematics to practical AI applications in healthcare, natural language processing, and related fields.[13] Through DeepLearning.AI, Ng has consistently argued that broad access to AI education is essential to ensuring that the technology's benefits are distributed widely rather than concentrated within a small number of organizations or geographic regions.

Landing AI

Ng also founded Landing AI, a company focused on helping established enterprises in manufacturing, agriculture, and healthcare apply AI and computer vision to real operational problems. Landing AI has developed AI-powered inspection systems, predictive maintenance tools, and other industrial applications for companies across multiple sectors.[14] A central focus of the company has been the challenge of deploying AI systems in environments where labeled training data is scarce — a problem substantially different from the data-rich conditions typical of major internet companies. Landing AI has developed and publicized methodologies for small-data AI deployment that Ng has discussed in detail in public lectures and publications.

Views on artificial intelligence

AI and employment

Ng has written and spoken extensively about the economic effects of artificial intelligence on labor markets. He has pushed back against what he describes as an overstated narrative of mass technological unemployment, arguing in a 2025 LinkedIn post that fears of an AI-driven "jobpocalypse" are not supported by the evidence and that the technology is more likely to transform job roles than eliminate them wholesale.[15] In a 2025 interview with NBC News, he characterized current AI systems as inherently limited and argued that they would not replace human workers in the near term.[16] At the same time, he has consistently maintained that workforce retraining and expanded access to AI education are necessary to help workers adapt to an economy increasingly shaped by automation.

AGI timelines

Ng has been a prominent skeptic of near-term predictions regarding the development of artificial general intelligence (AGI). He has publicly described AGI as likely decades away and has cautioned against what he regards as premature or sensationalist forecasts about its imminent arrival. In a 2026 report, Ng stated that he expected the wait for AGI to span decades rather than years, placing him among researchers who believe current AI architectures remain far from general human-level cognition.[17] He has also argued in public statements on X (formerly Twitter) that concerns about existential risk from AGI, while not without merit, should not distract from the more immediate challenges posed by current AI systems, including algorithmic bias, data privacy, and labor market disruption.[18]

Ng has also urged people not to abandon technical education in response to AI's advances. In a 2024 LinkedIn post highlighted by LinkedIn News, he criticized advice discouraging people from learning to code, arguing that programming and quantitative skills remain essential in an AI-augmented economy.[19]

Personal life

Ng is married to Carol Reiley, a roboticist and entrepreneur who co-founded Drive.ai, a company focused on autonomous vehicle technology.<ref>{{cite news |last=Geron |first=Tomio |date=2015-08-11 |title=Andrew Ng And Carol Reiley Are Married |url=https://www.forbes.com/sites/tomiogeron/2015/08/11/andrew-ng-and-carol-reiley-

  1. ↑ MetzCadeCade"The Man Behind the Google Brain: Andrew Ng and the Quest for the New AI".Wired.2013-05-16.https://www.wired.com/2013/05/neuro-artificial-intelligence/.Retrieved 2026-02-26.
  2. ↑ MetzCadeCade"The Man Behind the Google Brain: Andrew Ng and the Quest for the New AI".Wired.2013-05-16.https://www.wired.com/2013/05/neuro-artificial-intelligence/.Retrieved 2026-02-26.
  3. ↑ MarkoffJohnJohn"How Many Computers to Identify a Cat? 16,000".The New York Times.2012-06-26.https://www.nytimes.com/2012/06/26/technology/in-a-big-network-of-computers-evidence-of-machine-learning.html.Retrieved 2026-02-26.
  4. ↑ MetzCadeCade"The Man Behind the Google Brain: Andrew Ng and the Quest for the New AI".Wired.2013-05-16.https://www.wired.com/2013/05/neuro-artificial-intelligence/.Retrieved 2026-02-26.
  5. ↑ LewinTamarTamar"Instruction for Masses Knocks Down Campus Walls".The New York Times.2012-03-04.https://www.nytimes.com/2012/03/05/education/moocs-large-courses-open-to-all-topple-campus-walls.html.Retrieved 2026-02-26.
  6. ↑ LewinTamarTamar"Two Stanford Professors With an Idea, a Start-Up and 1.7 Million Students".The New York Times.2012-07-17.https://www.nytimes.com/2012/07/18/education/mooc-providers-coursera-and-edx-plan-to-expand-globally.html.Retrieved 2026-02-26.
  7. ↑ RivardRyRy"Coursera's contractual demands".Inside Higher Ed.2013-07-08.https://www.insidehighered.com/news/2013/07/22/courseras-contract-provokes-concerns.Retrieved 2026-02-26.
  8. ↑ MarkoffJohnJohn"How Many Computers to Identify a Cat? 16,000".The New York Times.2012-06-26.https://www.nytimes.com/2012/06/26/technology/in-a-big-network-of-computers-evidence-of-machine-learning.html.Retrieved 2026-02-26.
  9. ↑ MarkoffJohnJohn"How Many Computers to Identify a Cat? 16,000".The New York Times.2012-06-26.https://www.nytimes.com/2012/06/26/technology/in-a-big-network-of-computers-evidence-of-machine-learning.html.Retrieved 2026-02-26.
  10. ↑ LukLorraineLorraine"Baidu Hires Andrew Ng as Chief Scientist".The Wall Street Journal.2014-05-16.https://www.wsj.com/articles/baidu-hires-andrew-ng-as-chief-scientist-1400239985.Retrieved 2026-02-26.
  11. ↑ MozurPaulPaul"Andrew Ng, a Pioneer in Machine Learning, Leaves Baidu".The New York Times.2017-03-22.https://www.nytimes.com/2017/03/22/technology/andrew-ng-baidu-artificial-intelligence.html.Retrieved 2026-02-26.
  12. ↑ LohrSteveSteve"Andrew Ng, AI Guru, Has a New Curriculum: Telling Businesses How to Use It".The New York Times.2018-01-23.https://www.nytimes.com/2018/01/23/technology/andrew-ng-artificial-intelligence.html.Retrieved 2026-02-26.
  13. ↑ LohrSteveSteve"Andrew Ng, AI Guru, Has a New Curriculum: Telling Businesses How to Use It".The New York Times.2018-01-23.https://www.nytimes.com/2018/01/23/technology/andrew-ng-artificial-intelligence.html.Retrieved 2026-02-26.
  14. ↑ SimoniteTomTom"Andrew Ng Has a Chatbot That Can Help Farms Use AI".Wired.2018-03-14.https://www.wired.com/story/andrew-ng-landing-ai-agriculture/.Retrieved 2026-02-26.
  15. ↑ "Busting the AI Jobpocalypse Myth", LinkedIn, Andrew Ng, 2025.
  16. ↑ "Andrew Ng says AI is 'limited,' won't replace humans anytime soon", NBC News, 2025.
  17. ↑ "AI Pioneer Andrew Ng Expects Decades-Long Wait For AGI", PYMNTS.com, 2026.
  18. ↑ "Another year of rapid AI advances", X (AndrewYNg), 2025.
  19. ↑ "Andrew Ng: Ignore Career Advice to Not Learn to Code", LinkedIn News, 2024.
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