Aug 2, 2026 · 39 min · 10 segments
Google DeepMind researchers introduce Gemini Robotics 2 and discuss whole-body intelligence, dexterity, multi-robot collaboration, and the path toward physical AGI. Carolina Parada, Stuart Bowers…
Carolina ParadaGuest
Logan KilpatrickHost
Kanishka RaoGuest
Jie TanGuest
Stuart BowersGuest
What we're building here is the intelligence layer to power any robot to do a broad range of useful tasks.
Actually, our team has been working towards general purpose robotics since the inception of the team.
And we had a long history of always thinking, how do we solve the problem from first principles in a way that doesn't just take shortcuts and tries to solve the entire problem.
And so the entire problem really means infusing a robot with like human level intelligence, right? So that it can understand the environment as you and I can, so that it can reason about what it means to complete a task.
And then it can actually take action with all the dexterity that us humans have and take for granted.
And the actual release that we're talking about today is the new package of Gemini Robotics 2 models, starting with the ER model, but a bunch of other stuff as well.
Do you want to talk through sort of the different models, the suite of models that are becoming available?
Yeah, so Gemini Robotics 2 essentially is bringing whole body intelligence to robots.
So what that means is that we're enabling a model that can understand where the entire, every part of the robot is in space and it can reason about doing more complicated tasks.
So like imagine that you get in your closet and you're trying to clean it up and put away all your clothes and your shoes.
Like that requires you to move your body in all kinds of ways, avoid obstacles, reach things high, pick things from the floor.
This is something that we couldn't really do before in a way that understands what's going on.
So we literally like put the robot in a garage and ask it like, can you please clean up this garage, right? Is that the
real prompt in those examples? It's literally just like, please clean my garage.
So then the robot needs to reason about what does it mean to clean up a garage? It needs to like think about, oh, I'm going to put all the cleaning supplies in the same place.
If something falls on the ground, it has to understand that and then go pick it up and then put it away.
What we're building here is the intelligence layer to power any robot to do a broad range of useful tasks.
Actually, our team has been working towards general purpose robotics since the inception of the team.
And we had a long history of always thinking, how do we solve the problem from first principles in a way that doesn't just take shortcuts and tries to solve the entire problem.
And so the entire problem really means infusing a robot with like human level intelligence, right? So that it can understand the environment as you and I can, so that it can reason about what it means to complete a task.
And then it can actually take action with all the dexterity that us humans have and take for granted.
And the actual release that we're talking about today is the new package of Gemini Robotics 2 models, starting with the ER model, but a bunch of other stuff as well.
Do you want to talk through sort of the different models, the suite of models that are becoming available?
Yeah, so Gemini Robotics 2 essentially is bringing whole body intelligence to robots.
So what that means is that we're enabling a model that can understand where the entire, every part of the robot is in space and it can reason about doing more complicated tasks.
So like imagine that you get in your closet and you're trying to clean it up and put away all your clothes and your shoes.
Like that requires you to move your body in all kinds of ways, avoid obstacles, reach things high, pick things from the floor.
This is something that we couldn't really do before in a way that understands what's going on.
So we literally like put the robot in a garage and ask it like, can you please clean up this garage, right? Is that the
real prompt in those examples? It's literally just like, please clean my garage.
So then the robot needs to reason about what does it mean to clean up a garage? It needs to like think about, oh, I'm going to put all the cleaning supplies in the same place.
If something falls on the ground, it has to understand that and then go pick it up and then put it away.
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