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Episode Details
EPISODE INFO
- Released
- June 3, 2019
- Duration
- 1h 10m
- Channel
- Lex Fridman Podcast
- Watch on YouTube
- ▶ Open ↗
EPISODE DESCRIPTION
Rajat Monga is an Engineering Director at Google, leading the TensorFlow team. Thank you for listening ❤ Check out our sponsors: https://lexfridman.com/sponsors/ep22-sb See below for timestamps, and to give feedback, submit questions, contact Lex, etc. *CONTACT LEX:* *Feedback* - give feedback to Lex: https://lexfridman.com/survey *AMA* - submit questions, videos or call-in: https://lexfridman.com/ama *Hiring* - join our team: https://lexfridman.com/hiring *Other* - other ways to get in touch: https://lexfridman.com/contact *OUTLINE:* 0:00 - Introduction 1:17 - Google Brain early days 4:47 - TensorFlow early days - open sourcing, etc 12:53 - TensorFlow growth 22:00 - Keras 26:24 - TensorFlow project management 37:10 - Competition and PyTorch 39:48 - TensorFlow 2.0 51:20 - Building a good software engineering team 1:03:48 - Search ads and paying for content 1:08:43 - Using TensorFlow on a budget 1:10:16 - How to get started with TensorFlow *PODCAST LINKS:*
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SPEAKERS
Lex Fridman
hostRajat Monga
guest
EPISODE SUMMARY
In this episode of Lex Fridman Podcast, featuring Lex Fridman and Rajat Monga, Rajat Monga: TensorFlow | Lex Fridman Podcast #22 explores Rajat Monga on TensorFlow’s evolution, ecosystem, and open-source impact Rajat Monga, engineering director at Google and co-founder of TensorFlow, discusses the origins of Google Brain, the motivation and risk behind open-sourcing TensorFlow, and how it rapidly became a global standard for deep learning. He explains key design decisions (graphs, production focus, eager execution), the integration of Keras, and the tension between research agility and enterprise stability. Monga outlines TensorFlow’s expanding ecosystem across cloud, mobile, browser, and specialized hardware, emphasizing modularity, usability, and community-driven growth. He also touches on team-building, hiring, and how competition from projects like PyTorch has shaped TensorFlow 2.0 and beyond.
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