Best not to underestimate the power of BRNs/RTX radar.
Its almost science fiction.
AI Podcast Transcript & Summary - Steven Brightfield: How Neuromorphic Computing Cuts Inference Power by 10x
"Well, we can classify objects now with radar in addition to detecting them. We can improve the tracking and the latency of these radars. But we can also make them a lot smaller, right? So it's that size weight and power. Can I put a radar in a robot?
So when it's hand has got a radar signal in it and it can basically navigate, you can paint the scene without a camera. You can use it like a camera to paint the scene and recognize and grasp things that a drone. You can fly it inside tunnels or buildings indoors. You can map out where you're going. We see this shrinking of the conventional radar technologies to really go into anything moving because it's all whether it works in the dark. And if it can replicate some of the things in vision, then, you know, you don't have to worry about rain and fog and all the issues that visual, you know, control of robots. Yeah. And are you working with robotic companies or is this still in the research room? It's still in the research.
We're working with companies that are creating components or solutions that go to the robotics companies. We are in active conversations with robotic companies today. And they're in evaluation of this, right? But what we decided was to create reference platforms that demonstrate these more holy rather than having a, you know, here's the algorithm go figured out.
We'll build a little prototype. So we're doing reference designs and radar."
My bold above.