[Animats]

You can re-quantize analog signals into a finite number of levels to prevent noise accumulation. That's how TLC (8 levels) and QLC (16 levels) flash memory cells work. The cells store an analog value, but it's forced to a value close to one of N discrete values. The same approach is used in modems.

Deep learning doesn't seem to need that much numerical precision. People started with 32-bit floats, then 16-bit floats, now sometimes 8-bit floats, and recently there are people talking up 2-bit trinary. The number of levels needed may not be too much for analog. If you have a regenerator once in a while to slot values back to the allowed discrete levels, you can clean up the noise. That's an analog to digital to analog conversion, of course.

That's not what these guys are talking about, as far as I can tell.