Episode
Rajat Monga: TensorFlow
1:11:06
Published: Mon Jun 03 2019
Description
Rajat Monga is an Engineering Director at Google, leading the TensorFlow team. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations.
Chapters
TensorFlow started as a proprietary machine learning library in Google and became an open source library in 2014, showcasing the success of open innovation and inspiring many companies to follow suit.
00:00 - 05:29 (05:29)
Summary
TensorFlow started as a proprietary machine learning library in Google and became an open source library in 2014, showcasing the success of open innovation and inspiring many companies to follow suit.
EpisodeRajat Monga: TensorFlow
PodcastLex Fridman Podcast
In this episode, the host interviews Rajat Monga, the lead architect of TensorFlow, discussing the major design decisions made in the development of TensorFlow and the influence of other machine learning frameworks.
05:29 - 12:50 (07:21)
Summary
In this episode, the host interviews Rajat Monga, the lead architect of TensorFlow, discussing the major design decisions made in the development of TensorFlow and the influence of other machine learning frameworks.
EpisodeRajat Monga: TensorFlow
PodcastLex Fridman Podcast
Since the open sourcing of deep learning, it has grown substantially and is now no longer only for researchers.
12:50 - 18:49 (05:58)
Summary
Since the open sourcing of deep learning, it has grown substantially and is now no longer only for researchers. More developers are now able to apply it to various areas to deliver on what people want.
EpisodeRajat Monga: TensorFlow
PodcastLex Fridman Podcast
The integration of Keras into TensorFlow has not only been beneficial in terms of creating an easier way to organize data sets but has also opened up the possibility for machine learning to enter other industries, such as law.
18:49 - 26:19 (07:30)
Summary
The integration of Keras into TensorFlow has not only been beneficial in terms of creating an easier way to organize data sets but has also opened up the possibility for machine learning to enter other industries, such as law.
EpisodeRajat Monga: TensorFlow
PodcastLex Fridman Podcast
The collaborative design direction for open source projects involves the participation of several people in driving development and implementation, including Martin Wick and Francois, to accommodate and scale the ecosystem successfully.
26:19 - 31:20 (05:00)
Summary
The collaborative design direction for open source projects involves the participation of several people in driving development and implementation, including Martin Wick and Francois, to accommodate and scale the ecosystem successfully.
EpisodeRajat Monga: TensorFlow
PodcastLex Fridman Podcast
The usage of TensorFlow goes beyond researchers and is now widely used by production teams, with the push towards enabling others to build their own systems through TensorFlow 2.0.
31:21 - 36:16 (04:54)
Summary
The usage of TensorFlow goes beyond researchers and is now widely used by production teams, with the push towards enabling others to build their own systems through TensorFlow 2.0.
EpisodeRajat Monga: TensorFlow
PodcastLex Fridman Podcast
The transition to Web 3.0 brings about several opportunities such as enabling the development of new things and starting with a clean slate.
36:17 - 48:07 (11:49)
Summary
The transition to Web 3.0 brings about several opportunities such as enabling the development of new things and starting with a clean slate. The restructuring of monolithic systems into more modular ones also allows for the building of more efficient products by other organizations in the ecosystem.
EpisodeRajat Monga: TensorFlow
PodcastLex Fridman Podcast
The importance of cohesion across programming teams can affect the delivery of a project.
48:07 - 52:31 (04:24)
Summary
The importance of cohesion across programming teams can affect the delivery of a project. Embracing change is necessary and will occur while combining eager execution and graphs in natural programming languages.
EpisodeRajat Monga: TensorFlow
PodcastLex Fridman Podcast
Google's hiring process includes evaluating candidates not only on their technical skills, but also on their cultural fit.
52:31 - 59:10 (06:38)
Summary
Google's hiring process includes evaluating candidates not only on their technical skills, but also on their cultural fit. This approach has helped the company build a strong team with diverse skills and experiences.
EpisodeRajat Monga: TensorFlow
PodcastLex Fridman Podcast
The TensorFlow 2.0 team discusses the challenges of balancing deadlines and quality in software development and mentions the importance of finding a balance.
59:11 - 1:03:50 (04:39)
Summary
The TensorFlow 2.0 team discusses the challenges of balancing deadlines and quality in software development and mentions the importance of finding a balance. They also mention their strategy of releasing frequent updates to improve the product.
EpisodeRajat Monga: TensorFlow
PodcastLex Fridman Podcast
The podcast discusses the technical and revenue implications of ads on the internet and whether a mix of ad-supported and revenue-based models can be achieved, while also addressing the issue of annoying ads that pop up during browsing.
1:03:50 - 1:10:14 (06:23)
Summary
The podcast discusses the technical and revenue implications of ads on the internet and whether a mix of ad-supported and revenue-based models can be achieved, while also addressing the issue of annoying ads that pop up during browsing.
EpisodeRajat Monga: TensorFlow
PodcastLex Fridman Podcast
Rajit Shah discusses the benefits of paid services versus free services for exploring machine learning and TensorFlow, and encourages beginners to start by exploring tutorials and guides on the TensorFlow website.
1:10:14 - 1:10:55 (00:41)
Summary
Rajit Shah discusses the benefits of paid services versus free services for exploring machine learning and TensorFlow, and encourages beginners to start by exploring tutorials and guides on the TensorFlow website.