Afaik most low-power embedded ARM chips have more like 1Gflops than 10 - at least a few years ago, most didn’t even have a dedicated floating point unit, and you could probably couldn’t even get 100Mflops out of them.
Also, this is somewhat beside the point but if you tried to distribute any ML across such chips, you’d have enough latency problems ect. that they don’t fully count towards “compute capacity for mid-to-large AIs”
Afaik most low-power embedded ARM chips have more like 1Gflops than 10 - at least a few years ago, most didn’t even have a dedicated floating point unit, and you could probably couldn’t even get 100Mflops out of them.
Also, this is somewhat beside the point but if you tried to distribute any ML across such chips, you’d have enough latency problems ect. that they don’t fully count towards “compute capacity for mid-to-large AIs”