Practical AI AutoML and AI at Google
Sep 9, 2019
Sherol Chen, a machine learning developer at Google, shares her journey into AI, starting from her childhood passion for gaming. She dives into how different AI teams within Google collaborate and explains the practical applications of AutoML. Listeners will learn step-by-step how to get started with AutoML, including dataset preparation and model training. Sherol also highlights the balance between user-friendly interfaces and technical expertise, making AI more accessible.
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From Nintendo to Google AI
- Sherol Chen's journey into AI began with video games, sparking a fascination with virtual worlds.
- This led her to study AI and storytelling, eventually landing an internship at Google that changed her perspective on impact.
Impact in Academia vs. Industry
- Academia's impact involves research and publications, while industry focuses on broader user engagement and product development.
- Sherol's initial estimate of YouTube's user base (10,000) during her Google interview highlights the difference in scale between academia and industry.
Google's AI Ecosystem
- Google's AI efforts are divided between research (Google AI/Brain) and product development (Google Cloud).
- TensorFlow, developed by Google Brain, is a key tool within this ecosystem, facilitating both research and product applications.