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Leader in AI
Andrew Yan-Tak Ng
(Chinese: 吳恩達; born April 18, 1976)
Andrew Ng is a British-American computer scientist and technology entrepreneur, best known for his influential work in machine learning and artificial intelligence (AI).
He was the co-founder and head of Google Brain, where he led pioneering work in large-scale deep learning. He also served as the Chief Scientist at Baidu, where he built and led the company’s AI Group into a team of several thousand people.
Ng is currently an adjunct professor at Stanford University, where he was formerly an associate professor and Director of the Stanford AI Lab (SAIL).
He is a major figure in online education, having co-founded Coursera and DeepLearning.AI, platforms that have helped democratize AI education. Through these efforts, he has taught over 8 million students worldwide, making AI knowledge accessible to learners globally.
Andrew Ng has been widely recognized for his contributions:
- Named to Time magazine's 100 Most Influential People (2012)
- Featured in Fast Company’s Most Creative People (2014)
- Included in Time100 AI: Most Influential People in AI (2023)
In 2018, Ng launched the AI Fund, a $175 million investment initiative supporting AI startups. He also founded Landing AI, which develops AI-powered SaaS tools to help industries implement AI solutions effectively.
Most recently, on April 11, 2024, Amazon appointed Andrew Ng to its Board of Directors, further highlighting his global influence in technology and business.
Early Life and Education – Andrew Yan-Tak Ng
(Chinese: 吳恩達; born April 18, 1976)
Andrew Ng was born in London, United Kingdom, in 1976 to Ronald Paul Ng, a hematologist and lecturer at UCL Medical School, and Tisa Ho, an arts administrator affiliated with the London Film Festival. Both of his parents were immigrants from Hong Kong. He has at least one sibling.
Ng spent his early childhood in Hong Kong, where he began learning the basics of programming at the age of six using instructional books. In 1984, his family moved to Singapore, where he attended and later graduated from Raffles Institution.
During high school, Ng demonstrated extraordinary mathematical aptitude and was awarded a Silver Medal at the International Mathematical Olympiad.
Academic Background
- 1997: Earned a triple major undergraduate degree in Computer Science, Statistics, and Economics from Carnegie Mellon University (CMU), Pittsburgh, Pennsylvania.
- 1996–1998: Conducted research in reinforcement learning, model selection, and feature selection at AT&T Bell Labs.
- 1998: Completed a Master's degree in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology (MIT). At MIT, he developed the first publicly available, automatically indexed web search engine for academic papers, a forerunner to CiteSeerX.
- 2002: Earned a Ph.D. in Computer Science from the University of California, Berkeley, under the supervision of Michael I. Jordan. His dissertation, “Shaping and Policy Search in Reinforcement Learning”, is still widely cited.
Academic & Professional Career
- 2002: Began as an Assistant Professor at Stanford University.
- 2009: Promoted to Associate Professor and became Director of the Stanford Artificial Intelligence Lab (SAIL).
- Currently serves as an Adjunct Professor at Stanford.
Personal Life
Andrew Ng resides in Los Altos Hills, California.
He married Carol E. Reiley, an entrepreneur and AI roboticist, in 2014. The couple has two children:
- A daughter, born in 2019
- A son, born in 2021
In 2023, the MIT Technology Review referred to Ng and Reiley as an "AI power couple", highlighting their influence in the global AI space.
Academic Career and Contributions to Online Education – Andrew Yan-Tak Ng
Andrew Ng is a professor at Stanford University, affiliated with both the Department of Computer Science and the Department of Electrical Engineering. He previously served as the Director of the Stanford Artificial Intelligence Laboratory (SAIL), where he mentored students and conducted research in machine learning, data mining, and big data.
One of Ng’s most impactful contributions to academia is his Stanford course CS229: Machine Learning, which has become the most popular course on campus, with over 1,000 students enrolling in some years.
Pioneer in Online Education
In 2012, Ng co-founded Coursera alongside fellow Stanford computer scientist Daphne Koller. The platform was created to make high-quality education accessible to everyone, anywhere in the world, offering free and paid online courses from top universities.
Coursera gained immediate traction:
- Ng's CS229A course attracted over 100,000 students upon launch.
- Today, Coursera has enrolled millions of learners, making it one of the leading MOOC (Massive Open Online Course) platforms globally.
As of 2020, three of the top Coursera courses were authored by Ng:
- Machine Learning (#1)
- AI for Everyone (#5)
- Neural Networks and Deep Learning (#6)
Early Advocate of GPU Computing in AI
In 2008, Ng’s research group at Stanford was among the first in the U.S. to promote the use of GPUs (Graphics Processing Units) for deep learning. At the time, this was considered a risky and unconventional approach. However, Ng foresaw that using GPUs could significantly accelerate training of statistical models, solving major bottlenecks in scaling up machine learning on large datasets.
His early advocacy laid the groundwork for what is now standard practice—GPUs are a cornerstone of modern AI infrastructure.
Advocate of High-Performance Computing (HPC)
Since 2017, Andrew Ng has also been a vocal proponent of using high-performance computing (HPC) to scale deep learning and speed up innovation in the AI field. He emphasizes the importance of infrastructure in achieving breakthroughs and encourages researchers and companies to invest in computational efficiency alongside algorithmic progress.
Industry Leadership and Entrepreneurial Ventures – Andrew Yan-Tak Ng
From 2011 to 2012, Andrew Ng worked at Google, where he founded and directed the Google Brain Deep Learning Project in collaboration with Jeff Dean, Greg Corrado, and Rajat Monga. The project played a pivotal role in integrating deep learning into Google’s products and research infrastructure.
In 2014, Ng joined Baidu as Chief Scientist, where he led groundbreaking research in big data and artificial intelligence. At Baidu, he:
- Established multiple AI research teams focused on areas such as facial recognition and Melody, an AI chatbot for healthcare.
- Spearheaded the development of DuerOS, Baidu’s AI platform for voice-activated services and smart devices.
- Drove innovation that temporarily positioned Baidu ahead of even Google in key areas of AI research and product development.
In March 2017, Ng announced his resignation from Baidu to pursue new ventures in AI.
Founding New AI Initiatives
Soon after leaving Baidu, Ng launched a series of influential AI ventures:
- DeepLearning.AI: An online education platform offering a popular series of deep learning courses, including the AI for Good Specialization.
- Landing AI: Provides AI-powered SaaS products aimed at helping manufacturers adopt computer vision technologies for defect detection and process automation.
In January 2018, Ng introduced the AI Fund, an early-stage venture capital fund with an initial raise of $175 million, dedicated to incubating and investing in AI startups across various sectors.
In November 2021, Landing AI secured a $57 million Series A funding round, led by McRock Capital, to expand its impact in the manufacturing sector and promote the adoption of AI-powered computer vision.
Global Impact
In October 2024, Ng’s AI Fund made its first investment in India, backing Jivi, an AI healthcare startup. Jivi uses AI for:
- Diagnosing medical conditions
- Providing treatment recommendations
- Automating administrative tasks in healthcare delivery
This strategic investment reflects the growing potential of India's AI sector, which is projected to reach $22 billion by 2027.
Research Contributions and Technical Innovations – Andrew Yan-Tak Ng
Andrew Ng is globally recognized as one of the most influential and prolific computer scientists of the 21st century. His research spans several key areas in artificial intelligence, including:
- Machine Learning
- Deep Learning
- Machine Perception
- Computer Vision
- Natural Language Processing (NLP)
Ng has received multiple best paper awards at top-tier academic conferences, and his work has had a profound impact on AI, robotics, and computer vision.
Academic Research Highlights
- During graduate school, Ng co-authored the seminal paper that introduced Latent Dirichlet Allocation (LDA) alongside David M. Blei and Michael I. Jordan. Though Ng's Ph.D. thesis focused on reinforcement learning for drones, the LDA paper became one of the most highly cited papers in machine learning.
- He was the lead scientist on the Stanford Autonomous Helicopter project, which built one of the most capable autonomous helicopters of its time.
- Ng also spearheaded the STAIR (Stanford Artificial Intelligence Robot) project. This research laid the foundation for the Robot Operating System (ROS)—now the world’s most widely used open-source robotics framework.
- His vision of building general-purpose AI robots for home use inspired Scott Hassan to support the venture, which led to the creation of Willow Garage, a robotics research lab.
- Ng contributed to the Stanford WordNet project, where machine learning was used to extend the Princeton WordNet lexical database originally created by Christiane Fellbaum.
Google Brain and Major AI Breakthroughs
In 2011, Andrew Ng founded the Google Brain Project at Google, aiming to build large-scale deep neural networks using Google's powerful distributed computing infrastructure.
Key achievements include:
- Training a neural network using deep learning algorithms across 16,000 CPU cores.
- The model was able to learn to recognize cats simply by watching YouTube videos—without being told what a cat was. This became a landmark demonstration of unsupervised learning in AI.
- The innovations from Google Brain were later deployed in several Google products, including the Android operating system’s speech recognition system.
Pioneer of the MOOC Movement – Andrew Yan-Tak Ng
In 2011, Stanford University launched three of the first-ever Massive Open Online Courses (MOOCs), marking a transformative moment in digital education. These courses were:
- Machine Learning (CS229a) – taught by Andrew Ng
- Artificial Intelligence – taught by Sebastian Thrun and Peter Norvig
- Databases – taught by Jennifer Widom
This groundbreaking initiative laid the foundation for the modern MOOC movement, emphasizing scale (reaching hundreds of thousands of learners) and universal accessibility.
- Ng's machine learning course quickly became the most popular and influential.
- The AI course by Thrun and Norvig led to the creation of Udacity, while Ng’s success would inspire the founding of Coursera in 2012.
Global Impact on AI Education
Though the MOOC concept had been explored before 2012, Stanford's 2011 offerings were the first to achieve global reach at scale, catalyzing a revolution in online education.
By 2023, Andrew Ng had significantly expanded access to AI education:
- Over 8 million learners worldwide have taken his courses.
- His educational platforms—Coursera and DeepLearning.AI—remain among the most widely used AI learning resources globally.
Ng's leadership has made him one of the most influential educators in computer science, credited with democratizing AI and machine learning education for students, professionals, and institutions around the world.
Early Online Education Initiatives and the Birth of MOOCs – Andrew Yan-Tak Ng
In 2008, Andrew Ng launched the Stanford Engineering Everywhere (SEE) program, which published a series of free online Stanford courses for public access. Among these was his course on "Machine Learning", which included full video lectures, course notes, assignments, and solutions based on Stanford’s CS229 curriculum.
Unlike traditional open educational resources, SEE aimed to offer a comprehensive course experience, similar in ambition to MIT’s OpenCourseWare but with a more structured and guided format. The SEE videos were viewed by millions globally, setting the stage for Ng’s future innovations in online learning technology.
Inspiration and Campus Collaboration
Ng drew inspiration from both within and outside Stanford:
- Internal collaborators included:
- Daphne Koller – co-developed blended learning experiences and a peer-grading system.
- John Mitchell – developed CourseWare, an early learning management system (LMS).
- Dan Boneh – applied machine learning to sync lecture videos and later taught cryptography on Coursera.
- Bernd Girod – contributed to ClassX, a multimedia platform for lecture recordings.
- External inspirations included:
- Sal Khan (Khan Academy) – for tablet-based teaching and scalable content delivery.
- lynda.com – for user-friendly instructional design.
- Stack Overflow – for its forum-based support model.
Between 2009 and 2011, Ng and colleagues recorded and uploaded hundreds of hours of lecture videos. He even tested early versions of recorded lessons with local high school students to refine best practices for engagement and clarity.
Launch of Stanford MOOCs
In October 2011, Ng released an applied version of his machine learning class (CS229a) through ml-class.org, an experimental online platform. The course featured:
- Interactive quizzes
- Graded programming assignments
- Peer discussion forums
It attracted over 100,000 students, becoming one of the first and most successful MOOCs by a Stanford professor.
Following its success:
- Two additional MOOCs were launched:
- db-class.org (Databases, taught by Jennifer Widom)
- ai-class.org (Artificial Intelligence, taught by Sebastian Thrun and Peter Norvig)
- These platforms were developed by Stanford students including Frank Chen, Jiquan Ngiam, Chuan-Yu Foo, and Yifan Mai.
- The courses ran for 10 weeks, with over 40,000 students receiving Statements of Accomplishment.
Founding of Coursera
The widespread impact of these initial MOOCs led Ng and Daphne Koller to co-found Coursera in 2012, a platform that would go on to revolutionize global access to higher education.
By 2019, Ng's courses remained Coursera’s most popular:
- Machine Learning (#1)
- Neural Networks and Deep Learning (#2)
His commitment to open access and quality learning materials has helped millions of learners worldwide gain foundational and advanced knowledge in artificial intelligence.
Post-Coursera Work and Continued AI Advocacy – Andrew Yan-Tak Ng
In 2019, Andrew Ng launched a new online course titled “AI for Everyone”, aimed at a non-technical audience. The course was designed to:
- Help individuals understand the real-world impact of AI on business and society
- Outline both the benefits and potential costs of AI adoption
- Empower learners and companies to navigate the AI-driven technological revolution
The course gained wide recognition for demystifying AI concepts and became one of the top-rated courses on Coursera.
Venture Capital & Leadership Roles
Andrew Ng has continued to shape the AI landscape not only through education but also through strategic investments and advisory roles:
Woebot Labs
Ng serves as Chair of the Board for Woebot Labs, a company focused on mental health solutions using data science and AI.
- Woebot provides an AI-powered therapy chatbot designed to deliver cognitive behavioral therapy (CBT) to users.
- It is used to help manage depression, anxiety, and other mental health conditions.
Drive.ai
Ng was also a member of the Board of Directors at Drive.ai, a company specializing in autonomous vehicle technology.
- Drive.ai developed AI systems for self-driving cars and was acquired by Apple in 2019, reinforcing Apple’s entry into the self-driving space.
Landing AI and Democratizing AI Access
Through Landing AI, Ng has taken on the mission of lowering the barrier to AI adoption for enterprises and developers—particularly in industries that are traditionally underserved by AI, such as manufacturing.
Landing AI focuses on:
- Providing AI-powered SaaS tools for computer vision and industrial automation
- Enabling small- and medium-sized businesses to implement AI solutions without the need for massive datasets or in-house AI teams
Ng continues to advocate for making AI practical, inclusive, and broadly accessible, both through education and business innovation.
Academic Contributions and Recognition – Andrew Yan-Tak Ng
Andrew Ng is a prolific researcher and thought leader in artificial intelligence. He is the author or co-author of over 300 publications across robotics, machine learning, deep learning, computer vision, and related fields.[57] His influential research has been widely cited and frequently featured in scientific journals, industry reviews, and press releases.[58]
Awards and Honors
Ng has received numerous prestigious awards throughout his academic and professional career, recognizing his leadership in both AI innovation and education:
- 1995 – Bell Atlantic Network Services Scholarship
- 1995, 1996 – Microsoft Technical Scholarship Awards
- 1996 – Andrew Carnegie Society Scholarship
- 1998–2000 – Berkeley Fellowship
- 2001–2002 – Microsoft Research Fellowship
- 2007 – Alfred P. Sloan Research Fellowship, Sloan Foundation Faculty Fellowship
- 2008 – MIT Technology Review TR35, Innovators Under 35
- 2009 – IJCAI Computers and Thought Award (highest AI award under age 35)
- 2009 – Vance D. & Arlene C. Coffman Faculty Scholar Award
- 2013 – Time Magazine, 100 Most Influential People
- 2013 – Fortune’s 40 Under 40
- 2013 – CNN 10: Thinkers
- 2014 – Fast Company, Most Creative People in Business
- 2015 – World Economic Forum, Young Global Leaders
- 2023 – Time Magazine, AI 100 Most Influential People
- 2024 – Honorary Fellowship, Royal Statistical Society
Editorial and Conference Roles
Andrew Ng has played major roles in shaping academic discourse in AI through his editorial and reviewing work:
- Editor – Journal of Artificial Intelligence Research (JAIR)
- Associate Editor – IEEE Robotics and Automation Society Conference Editorial Board (ICRA)
- Co-referee – For hundreds of publications at leading conferences such as NeurIPS, ICML, CVPR, and others
Speaking Engagements and Global Influence
Ng has been an invited keynote speaker at some of the world’s most respected institutions and organizations, including:
- NASA, Google, Microsoft, Lockheed Martin, Max Planck Society
- Prestigious universities including: Stanford, MIT, Princeton, Cornell, UC Berkeley, UPenn, among others
- Delivered lectures globally in Spain, Germany, Israel, China, Korea, and Canada
Writing and Public Thought Leadership
Ng has written articles and contributed thought leadership to top publications and media platforms:
- Harvard Business Review
- HuffPost
- Slate
- Apple News
- Quora Sessions / Twitter
He also curates and authors The Batch, a weekly digital AI newsletter that offers analysis, insights, and updates on the AI industry.
Publications and Authored Works
Andrew Ng has authored and contributed to several influential publications aimed at democratizing AI knowledge and helping businesses navigate the age of artificial intelligence:
- Machine Learning Yearning (2018):
A practical, strategic guide for engineers and technical managers building AI systems. The book focuses on how to structure machine learning projects and was distributed for free to promote accessible AI education. - AI Transformation Playbook (2018):
Released in December 2018, this sequel to Machine Learning Yearning is geared toward non-technical leaders and executives, offering actionable advice for adopting and scaling AI within organizations. - Architects of Intelligence (2018):
Ng contributed a dedicated chapter to this book by futurist Martin Ford, alongside other prominent AI pioneers. The book explores the future of AI through interviews with the visionaries building it.
Views on AI Ethics, Regulation, and the Future of Work
Andrew Ng has consistently advocated for a pragmatic and human-centered approach to AI development and policy:
- On the future of work:
Ng argues that the real threat from AI isn't science fiction scenarios involving killer robots, but rather the impact on jobs and labor markets. He emphasizes that “rather than being distracted by evil killer robots, the challenge to labor caused by these machines is a conversation that academia, industry, and government should have.” - On democratizing AI:
A strong proponent of expanding global access to AI education, Ng believes that empowering individuals and communities to use AI tools is critical to building meaningful and beneficial applications at scale. - On AI regulation (Dec 2023, Financial Times):
Ng voiced concerns about proposed global AI regulations that could overburden small companies and stifle innovation, particularly in the open-source ecosystem. He warned that regulatory requirements like licensing, liability frameworks, and reporting mandates could discourage experimentation without significantly improving safety. He urged policymakers to adopt balanced, innovation-friendly regulations. - On California AI legislation (June 2024, Financial Times):
Ng criticized a proposed California bill that would have required developers to include "kill switches" and safety mechanisms for advanced AI models. He described the legislation as promoting “massive liabilities for science-fiction risks” and said it would "stoke fear in anyone daring to innovate.” Other experts echoed his concerns, citing the disproportionate burden on open-source developers and startups.
In September 2024, California Governor Gavin Newsom vetoed the bill, aligning with industry feedback.
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