[Luxonis-Brandon]

Thanks for the comments usrusr! And great points. So one of the things we did early-on is to prototype the whole flow to see if you could indeed get incredibly low false-positives. The key ended up being the combination of disparity depth (which gives over 1 million depth points) and neural inference so that the system can know incredibly granularly (i.e. within inches) the edges of things and their predictive trajectories.

So at the outset of this effort (back in 2017) such a computer-vision based device that was inexpensive and embeddable was impossible. The Movidius Myriad X came out, which has all the requisite CV/AI processing to make such a thing solvable... but there was no hardware/firmware/software/AI ecosystem which allowed producing such embedded spatial AI problems.

So we had to build that first to solve this safety problem and we're releasing it in conjunction with OpenCV as the OpenCV AI Kit (OAK). https://opencv.org/opencv-spatial-ai-competition/

So the `why` of this is it allows others to solve problems on embedded systems which were previously intractable. And there are a ton of them... the number of applications we've seen has blown our mind.

We'll have a KickStarter around this OpenCV AI Kit which will be going live on July 14th: https://www.kickstarter.com/projects/opencv/opencv-ai-kit

Thoughts?

Thanks, Brandon