Recent content by evalegend

A practical understanding of Make starts with knowing what the system does well, where it is unreliable, and how to validate the result. One important area is data quality. Define what a good result looks like before changing tools or settings, then test one variable at a time so you can tell...

When working with Edge AI Devices, the biggest gains usually come from treating it as a repeatable workflow rather than a one-off prompt or experiment. One important area is getting started. Define what a good result looks like before changing tools or settings, then test one variable at a time...