Andrew Ng

Andrew Ng has spent a quarter of a century sitting at the intersection of AI research, industrial deployment and mass education, and by 2026 no single figure has done more to widen the pool of people who actually know how to build machine-learning systems. Born in London to Hong Kong immigrant parents and raised partly in Hong Kong and Singapore before settling in the United States, Ng earned degrees from Carnegie Mellon, MIT and a PhD from the University of California, Berkeley, before joining the Stanford faculty, where he remains an adjunct professor.

His research career includes foundational work on reinforcement learning and, crucially, the 2011 founding of Google Brain, the deep-learning research group whose large-scale neural networks demonstrated that AI could learn to recognise concepts such as cats from unlabelled YouTube video — an early proof point for the scaling laws that now underpin the industry. He subsequently served as Chief Scientist at Baidu, where he built out the Chinese search giant's AI Group and pushed speech-recognition systems into wide deployment.

Ng's broader legacy, though, is educational. In 2012 he co-founded Coursera, the online learning platform that put university-calibre courses, including his own Stanford machine-learning class, in front of tens of millions of students worldwide. He followed that with deeplearning.ai, whose specialisations have become a rite of passage for engineers entering the field, and with the AI Fund, a venture studio he leads as managing general partner that incubates AI-native startups.

His current company, Landing AI, which he founded in 2017 and where he serves as executive chairman, focuses on making computer-vision and, increasingly, document- and agentic-AI tools usable by manufacturers and enterprises without large data-science teams — a 'data-centric AI' philosophy Ng has championed as a counterweight to purely model-centric approaches. Through 2026 the company has continued to expand its agentic document-extraction tools for enterprise automation, reflecting his consistent bet that practical, industry-specific tooling matters as much as frontier model research.

Ng is also one of the industry's more measured public voices, frequently pushing back against alarmist predictions of imminent super-intelligent risk while still urging responsible deployment. Between his academic pedigree, his entrepreneurial track record across Google, Baidu, Coursera and Landing AI, and an audience of millions of students and followers, few individuals have shaped as many careers — or as much of the world's practical AI capacity — as he has.