Dr. Fei-Fei Li

Professor & AI Pioneer at Stanford HAI / Former Google Cloud Chief AI Scientist

Known as the Godmother of AI; spearheaded ImageNet which sparked the current AI revolution; former Chief AI Scientist at Google Cloud, Director of Stanford AI Lab (SAIL), co-creator of Stanford's Human-Centered AI Institute; Time's 100 Most Influential in AI.

The Scientist The Visionary

Dimension Profile

Strategic Vision 90%

Execution & Craft 50%

Data & Experimentation 80%

Growth & Distribution 20%

Team & Leadership 50%

User Empathy & Research 60%

Key Themes

ImageNet and data-driven AI human-centered AI visual intelligence AI as double-edged sword technology as net positive training machines with massive data

Episode Summary

Dr. Fei-Fei Li, the Godmother of AI who spearheaded ImageNet and sparked the current AI revolution, shares the origin story of how realizing that AI needed massive clean-labeled data led to the breakthrough that underpins all modern AI. She articulates her human-centered AI philosophy — that there is nothing artificial about AI because it's made by and for people — and warns that while technology is a net positive, every advance is a double-edged sword society must wield responsibly.

Leadership Principles

→ There is nothing artificial about AI — it is inspired by people, created by people, and most importantly, it impacts people
→ Whatever AI does is up to us — technology is a net positive for humanity but every technology is a double-edged sword that we can screw up
→ AI needed a ton of clean-labeled data to get smarter — the breakthrough was realizing you need millions of examples to train computers on object concepts

Notable Quotes

"There is nothing artificial about AI. It's inspired by people. It's created by people, and most importantly, it impacts people."
— From her presentation to Congress on the human element of AI

"I do believe technology is a net positive for humanity, but I think every technology is a double-edged sword. If we're not doing the right thing as a society, as individuals, we can screw this up as well."
— On the responsibility that comes with AI advancement

"In order to train computers with tens and thousands of object concepts, you really need to show it millions of examples. A single object can have infinite possibilities that is shown on an image."
— On the core insight behind ImageNet that sparked the AI revolution

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