Founder of DeepLearning.AI and AI Fund managing general partner
Andrew Ng
Andrew Ng is an AI researcher, educator, and entrepreneur who founded DeepLearning.AI, co-founded Coursera, and teaches at Stanford University.
About Andrew Ng
Andrew Ng is an AI researcher, educator, and entrepreneur. He founded DeepLearning.AI, serves as managing general partner at AI Fund, and is an adjunct professor at Stanford University. His current work combines AI training with building and supporting AI businesses.
He co-founded Coursera, led the founding Google Brain team, and previously served as chief scientist at Baidu and director of the Stanford AI Lab. His research and teaching cover machine learning and practical AI applications. He earned his PhD at the University of California, Berkeley.
Mentioned in our coverage
47 articles name Andrew Ng, excluding author credits.
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- Top 10 AI Newsletters to Follow in 2026 →
There are hundreds of AI newsletters and most of them repackage the same three headlines. This is a manually researched, hands-on-reviewed ranking of the 10 worth your inbox in 2026 — who they're for, how often they send, and what makes each one different.
- An AI Agent "Apologized" for Being Away All Weekend. Here's Why. →
Rish Neynar gave a team of coding agents a Slack-style standup channel so they'd coordinate work. Within days, one agent was apologizing for being "away all weekend" and another had redesigned the company logo 2,500 times. The post hit 882K views for being funny — explainx.ai breaks down why it happened and what it means for anyone building multi-agent systems.
- Andrew Ng's AI Engineering Skills Map: The 4 Skills That Matter →
Andrew Ng and DeepLearning.AI mined over 10,000 job postings and dozens of expert interviews to identify four AI engineering skills every developer needs in 2026 — not just people with "AI Engineer" in their title. explainx.ai breaks down what each skill actually requires and how to start building it.
- How to Graph-Max with Codex and GPT-5.6 Sol →
Alex Kotliarskyi’s two-step “graph-max” method hit hundreds of thousands of views. Peter Steinberger asked if he’s a graph engineer now. explainx.ai maps the recipe, the sketch legend, and when graphs beat loops.
- Graphs vs. Loops: The Agentic AI Orchestration Debate, Explained →
A DeepLearning.AI course on turning raw data into knowledge graphs with multi-agent systems collided on X with Linear's launch of Loops — recurring autonomous agent workflows for bug triage and doc updates. The resulting debate over graphs versus loops for agent orchestration echoes a decades-old software engineering argument that keeps resurfacing under new names.
- X Rebuilds Its Android App From Scratch — What Changed and Why It Took a Year →