Exploring Real-World Computer Vision: Deployments, Edge Models, and Current Challenges

I've built a lot of ML systems over the years, mainly computer vision models optimised to run on mobile phones. For example, my previous company built the food recognition model for MyFitnessPal.

I'm interested in what people are actually deploying in industry now. Are edge models still a big part of your work, are you hosting your own models, or are you mostly sending requests to APIs? What's driving that choice?

More importantly, what's still a pain? I'd be interested in problems from current or recent projects that existing tools haven't solved well. Something that's cost you a lot of time, blocked delivery or needed an awkward workaround.

I'm looking for problems where I could build useful tooling, rather than guessing what people need. It would also be useful to know where you discuss this stuff or look for help. Are there particular forums or communities worth following?