Can you please provide any sort of justification for your (quite ridiculous) statement. We have quite a long history of signal processing migrating to digital precisely because it is better in every regard, INCLUDING POWER. Maaaaaybe, since AI neuromorphic-like circuits are quite fuzzy, they wouldnt require such strong noise resilience and precision, this could be a potential use case, but there is also a point of reliability and testability, which on these required scales for AI will be completely infeasible for analog circuits.

Low power inference chips already exist and digital computing uses exponentially less power every year.

The company (Mythic AI) in the article was featured on a Veritasium video[1] about analog computing.

The interesting part for analog is obviously going to be wear and repeatability, because the digital layer auto-corrects the errors until it becomes damaged and unusable clearly, while analog will slide off somewhat gracefully but you need a way to detect it happening multiple layers later.

AI is somewhat tolerant of errors since, the cumulative error across a lot of biases can approach zero if the errors are random.

[1] - https://www.youtube.com/watch?v=GVsUOuSjvcg#t=15m44s

IMNSHO, AI will the catalyst for going to nuclear power.

No. Today you can get a netbook which can be powered by a phone charger.