Episode Description
Paige Bailey is a developer relations engineering lead at Google DeepMind. She's a geophysicist-turned-AI-engineer who was once told by her professors that building open-source libraries was a waste of time. We talk about her path from planetary science to TensorFlow, why statisticians have a hidden edge in the age of AI, and what it means to be a curious generalist when the cost of building software is approaching zero. Bonus: installing solar-powered silent-film birdhouses as street art in San Francisco.
What's inside
- From planetary science to TensorFlow, before it was GPU-capable
- Geophysicists as early GPU adopters
- The professors who said open-source wasn’t “real science”
- Building silent-film birdhouses as San Francisco street art
- Hiding Gemini API tests inside whimsical side projects
- The right-tool-for-the-job case for mixing AI models
- Why “taste” is the skill that matters when code costs nothing