On a slight tangent, I do wonder if the Raspberry Pi is the right dev board for running compute-intensive AI models. It is cheap but the real hero of the Pi is the Broadcom SoC. Where as there are other dev boards out there - lots of them in fact - which would have a faster CPU, dedicated ethernet bus (even gigabit ethernet - which would be better for clustering too), etc.
I do love my Pis (I have a few of them) but if you're having to overclock the thing and then strap on a CPU fan to make the Pi even viable for running compute-intensive AI models then perhaps the exercise might have been better suited for running on another piece of hardware instead?
FPGA comes to mind. I think AWS has the right idea with cloud based FPGA programming.
I see general IA coming first in the form of many neural networks working together. Being able to optimize each sector for its own processing needs seems like both the most power efficient and performance optimal solution.
I do love my Pis (I have a few of them) but if you're having to overclock the thing and then strap on a CPU fan to make the Pi even viable for running compute-intensive AI models then perhaps the exercise might have been better suited for running on another piece of hardware instead?