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Pete Florence: Dense Visual Representations, NeRFs, and LLMs for Robotics
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Pete Florence: Dense Visual Representations, NeRFs, and LLMs for Robotics

On how robotics can benefit from dense visual representations, neural radiance fields, and large language models

In episode 54 of The Gradient Podcast, Andrey Kurenkov speaks with Pete Florence.

Note: this was recorded 2 months ago. Andrey should be getting back to putting out some episodes next year.

Pete Florence is a Research Scientist at Google Research on the Robotics at Google team inside Brain Team in Google Research. His research focuses on topics in robotics, computer vision, and natural language -- including 3D learning, self-supervised learning, and policy learning in robotics. Before Google, he finished his PhD in Computer Science at MIT with Russ Tedrake.

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Outline:

  • (00:00:00) Intro

  • (00:01:16) Start in AI

  • (00:04:15) PhD Work with Quadcopters

  • (00:08:40) Dense Visual Representations 

  • (00:22:00) NeRFs for Robotics

  • (00:39:00) Language Models for Robotics

  • (00:57:00) Talking to Robots in Real Time

  • (01:07:00) Limitations

  • (01:14:00) Outro

Papers discussed:

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