If you think about it deep learning is the triumphant return of analog computing.
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“Digital” is etymologically related to counting on fingers
“Analogue” is etymologically related to seeing in patterns/proportions
The symbolic vs subsymbolic divide is superficial, the discrete vs continuous divide gets closer, but the essence is how you measure the real
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Digital operations measure things in terms of countable relations to an abstract, absolute standard. Analog operations measure things in terms of similarity relative to each other.
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Have you read _Mount Analogue_? Yet another unread book on my to read pile (that one's buried in storage). An odd little book, seems fascinating:
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