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Jeff Dean

08/08/17

@ Y Combinator

We aim to establish TensorFlow as a common platform for expressing various machine learning ideas, ensuring it can be used for deep learning, perception problems, and language understanding.

Video

Jeff Dean’s Lecture for YC AI

@ Y Combinator

Jeff Dean’s Lecture for YC AI

08/08/17

Related Takeaways

Jeff Dean

08/08/17

@ Y Combinator

TensorFlow is our second-generation system designed to tackle deep learning and machine learning problems, built to be an open-source platform for global collaboration.

Jeff Dean

08/08/17

@ Y Combinator

We conduct long-term research independent of any particular application and build open-source systems to assist with our research and deployment of machine learning models, like TensorFlow.

Jeff Dean

08/08/17

@ Y Combinator

TensorFlow is increasingly being used in machine learning classes at top universities, illustrating core concepts in the curriculum.

Jeff Dean

08/08/17

@ Y Combinator

The growth in interest for TensorFlow has led to nearly a thousand non-Google contributors globally, enhancing the system through feature additions and bug fixes.

Jeff Dean

05/12/25

@ Sequoia Capital

The TPU program was initiated to meet the demand for high compute power for inference and training in AI applications.

Scott Clark

05/23/25

@ a16z

Technology executives need to create a uniform interface for AI systems that provides value and encourages developers to adopt centralized platforms.

Jeff Dean

08/08/17

@ Y Combinator

We made these chips programmable via TensorFlow, allowing models to run on CPUs, GPUs, or TPUs with minimal modifications.

Lex Fridman Cast

02/03/25

@ Lex Fridman

Open source models like Tulu aim to provide accessible tools for fine-tuning AI models to specific domains, promoting innovation.

Lin Qiao

05/19/25

@ Sequoia Capital

We have developed a self-serve platform that allows developers to easily tune AI applications for speed and quality, facilitating rapid scaling and experimentation.