Robotics
a place to discuss robotics, how to build them, papers, tutorials, the consequences, hands on demos and more
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On the Jetson NVIDIA Thor AGX platform 2070 FP4 teraflops is pretty insane. You get a general sense that NVIDIA is just completely betting 100% on end-to-end reinforcement learning policies for physical AI. And if you look at companies like Physical Intelligence with their Pi0 foundational model and how much NVIDIA is investing into Omniverse and NVIDIA Isaac Sim for training using behavior cloning and imitation learning. It's super interesting because it shows how they are definitely buying into being able to run a lot of these end-to-end models out of the box But still a lot of safety concerns for me mostly from a safety-critical systems perspective. My general feeling around this is that the solution is relatively simple: Create a factory where humans can't enter because it's dangerous and let the vehicles and robots go crazy doing whatever they want in them. That's probably the near-term solution to not having a hierarchical system of models. On the physical side, there are two things: 1) i think the actual next bottleneck is also actuators. Actuator prices are going to have to come down, which the supply chain for actuators is owned by China pretty much, 90+. So I think that's why you see Unitree and other robotics companies backed heavily by state capital in China. 2) It's battery density. The watts per kilogram per dollar needs to still fall significantly more in order to create vehicles and robots that are going to be able to do hours and hours of work. It's definitely true that you can get the robots to exchange their batteries for themselves. But that being said, it's going to take significantly more effort and cost because you're going to have to swap batteries. You're just not at the Tesla level EV yet in terms of watts per kilogram. Energy density is key. https://x.com/apptronik/status/1960013664846852128?s=4 https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-thor/
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