Fully autonomous robots are much closer than you think – Sergey Levine
Sergey Levine is one of the world’s top robotics researchers and co-founder of Physical Intelligence. He thinks we’re on the cusp of a “self-improvement flywheel” for general-purpose robots. His median estimate for when robots will be able to run households entirely autonomously? 2030.
If Sergey’s right, the world 5 years from now will be an *insanely* different place than it is today. This conversation focuses on understanding how we get there: we dive into foundation models for robotics, and how we scale both the data and the hardware necessary to enable a full-blown robotics explosion.
𝐄𝐏𝐈𝐒𝐎𝐃𝐄 𝐋𝐈𝐍𝐊𝐒
* Transcript: https://www.dwarkesh.com/p/sergey-levine
* Apple Podcasts: https://podcasts.apple.com/us/podcast/fully-autonomous-robots-are-much-closer-than-you-think/id1516093381?i=1000726524050
* Spotify: https://open.spotify.com/episode/1WpOKLN3vSvvWjrVDIJAyy?si=DPxf6K5BSBy5R4OYIqk8pQ
𝐒𝐏𝐎𝐍𝐒𝐎𝐑𝐒
* Labelbox provides high-quality robotics training data across a wide range of platforms and tasks. From simple object handling to complex workflows, Labelbox can get you the data you need to scale your robotics research. Learn more at https://labelbox.com/dwarkesh
* Hudson River Trading uses cutting-edge ML and terabytes of historical market data to predict future prices. I got to try my hand at this fascinating prediction problem with help from one of HRT’s senior researchers. If you’re curious about how it all works, go to https://hudson-trading.com/dwarkesh
* Gemini 2.5 Flash Image (aka nano banana) isn’t just for generating fun images — it’s also a powerful tool for restoring old photos and digitizing documents. Test it yourself in the Gemini App or in Google’s AI Studio: https://ai.studio/banana
To sponsor a future episode, visit https://dwarkesh.com/advertise
𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒
(00:00:00) – Timeline to widely deployed autonomous robots
(00:17:25) – Why robotics will scale faster than self-driving cars
(00:27:28) – How vision-language-action models work
(00:45:37) – Changes needed for brainlike efficiency in robots
(00:57:59) – Learning from simulation
(01:09:18) – How much will robots speed up AI buildouts?
(01:18:01) – If hardware’s the bottleneck, does China win by default?
Sergey Levine is one of the world’s top robotics researchers and co-founder of Physical Intelligence. He thinks we’re on the cusp of a “self-improvement flywheel” for general-purpose robots. His median estimate for when robots will be able to run households entirely autonomously? 2030.
If Sergey’s right, the world 5 years from now will be an *insanely* different place than it is today. This conversation focuses on understanding how we get there: we dive into foundation models for robotics, and how we scale both the data and the hardware necessary to enable a full-blown robotics explosion.
𝐄𝐏𝐈𝐒𝐎𝐃𝐄 𝐋𝐈𝐍𝐊𝐒
* Transcript: https://www.dwarkesh.com/p/sergey-levine
* Apple Podcasts: https://podcasts.apple.com/us/podcast/fully-autonomous-robots-are-much-closer-than-you-think/id1516093381?i=1000726524050
* Spotify: https://open.spotify.com/episode/1WpOKLN3vSvvWjrVDIJAyy?si=DPxf6K5BSBy5R4OYIqk8pQ
𝐒𝐏𝐎𝐍𝐒𝐎𝐑𝐒
* Labelbox provides high-quality robotics training data across a wide range of platforms and tasks. From simple object handling to complex workflows, Labelbox can get you the data you need to scale your robotics research. Learn more at https://labelbox.com/dwarkesh
* Hudson River Trading uses cutting-edge ML and terabytes of historical market data to predict future prices. I got to try my hand at this fascinating prediction problem with help from one of HRT’s senior researchers. If you’re curious about how it all works, go to https://hudson-trading.com/dwarkesh
* Gemini 2.5 Flash Image (aka nano banana) isn’t just for generating fun images — it’s also a powerful tool for restoring old photos and digitizing documents. Test it yourself in the Gemini App or in Google’s AI Studio: https://ai.studio/banana
To sponsor a future episode, visit https://dwarkesh.com/advertise
𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒
(00:00:00) – Timeline to widely deployed autonomous robots
(00:17:25) – Why robotics will scale faster than self-driving cars
(00:27:28) – How vision-language-action models work
(00:45:37) – Changes needed for brainlike efficiency in robots
(00:57:59) – Learning from simulation
(01:09:18) – How much will robots speed up AI buildouts?
(01:18:01) – If hardware’s the bottleneck, does China win by default?
