Hi Luke,

Really enjoyed another one of your videos, you've definitely got me experimenting more with edge compute and AI in my garden. I was wondering whether you’ve done much with NVIDIA Jetson boards? I think you mentioned having an older version in a previous video.

I got an Orin nano super developer kit since the higher-memory RPis doubling in the past year, while the Orin Nano/Orin Nano Super now seem surprisingly fairly static in price over that time period. What interests me is the possibility of using them for wildlife monitoring: running detection or ID models locally, collecting new field data, self labelling and training then using that data to periodically improve the model all on the edge.

I’m not sure whether full on-device training would be practical, but perhaps a more realistic workflow would be active learning or a teacher–student/pseudo-labelling setup: the device flags uncertain or interesting detections, those get reviewed or labelled, and the model is retrained or fine-tuned periodically self redeploying via scripts or a local model and agentic harness.

There also seems to be a good ecosystem of cameras and sensors around Jetson. I assume you find limitations in the Jetson boards for ecology/wildlife-monitoring projects?