First try and understand every symbol in the equation, there are cheat sheets online. Second, most math concepts have a wikipedia page you can read, go down those rabbit holes and sooner or later you will find common threads and start to build an understanding. Finally, just put the time in, math is like everything else and just takes lots and lots of practice.

The devil is in the details. Getting robots to work reliably in the gritty dirty environments of agtech is incredibly difficult. Manipulation, even with modern ML and CV, is still very difficult. Let's just say there is a reason there aren't a ton of robotics companies selling a product such as the one you suggested.

Having done ML consulting work through Upwork, my experience is the rate on Upwork is really low compared to what you can get through networks, especially remote Bay Area work. Most Upwork seems to be short timelines, small payouts, and competing against low cost international talent. Any tips for Upwork you can suggest?

I think Ray is great! But Ray will not click your GPUs into a motherboard, install linux on all the machines, setup nvidia-docker, power cycle if there are issues, periodically clear up space on hdds, etc. Its the non-software part of cluster management that ends up being the most annoying and time consuming.

Cloud is almost always better imo. At the small scale you can prototype quicker and spend less time messing with hardware by using cloud services. Once you actually need to scale your product then using a cloud solution makes it really easy. The "but its cheaper" argument gets less and less valid every year, and it often doesn't account for the time and effort spent setting up a local cluster.