And a general lack of reconfigurability to solve general problems. There’s been interest in analog neural networks for a long time.
Those problems you mention are important in music synthesis where people could live with limited reconfigurability but reliability is at a premium: synth players in early touring bands (e.g. Yes) had to be electronics technicians and instruments have to survive being packed in boxes and transported everywhere. The Yamaha DX-7 made FM synthesis mainstream because digital FM synthesis was absolutely reliable.
And a general lack of reconfigurability to solve general problems. There’s been interest in analog neural networks for a long time.
Those problems you mention are important in music synthesis where people could live with limited reconfigurability but reliability is at a premium: synth players in early touring bands (e.g. Yes) had to be electronics technicians and instruments have to survive being packed in boxes and transported everywhere. The Yamaha DX-7 made FM synthesis mainstream because digital FM synthesis was absolutely reliable.
Analog synths are a lot more reliable these days though.
In neutral networks, we seem to be pushing towards ever lower precision floats, and we use noise for all sorts of useful things.
Also true: all computing is analog computing.