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Respectfully, this is begging the question :) You're correct that neural networks don't encode information in the way current digital machines do (i.e. with ex
by _dps 10y ago
Respectfully, this is begging the question :)
You're correct that neural networks don't encode information in the way current digital machines do (i.e. with explicit records/files/etc encoded in bytes). I would disagree that this is the only useful view of information. And certainly, from a Shannon information perspective, the network structure contains information (in the Shannon sense) about the environment or problem for which it was optimized.
- lngnmn 10y ago> the network structure contains information (in the Shannon sense) about the environment ... the way a map represents a territory instead of how a guide book does ;) Or the way a 3D structure made out of the same 20 joined amino-acids could represent either an enzyme (the code) or a protein (the data) and that there is no distinction between code and data (which is the great insight realized in the original Lisp. It is not a coincidence that Lisp was the language or the classic AI. Sorry for the reminiscence - just love this part).