- #1
nomadreid
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First of all: I am not a programmer, I cannot read code, only have a background in pure mathematics, am looking for a very simplified summary ("for Dummies") of the way Deep Learning and similar AI routines handle sensor data. I looked at a few articles such as http://papers.www2017.com.au.s3-website-ap-southeast-2.amazonaws.com/proceedings/p351.pdf, but these are written for those who already understand the basic idea and wish to go into details. So, the question is such: I imagine (in my naïve approach) the computer-without-sensors to be composed of a (first-order) logic, and then the sensor data might be attached in one of two different ways (please hold your laughter for the moment):
(a) the coded sensor data provides constant values for variables in the logic, so that the whole thing remains purely syntactical, with truth predicates either implicit or explicit, or
(b) the sensor data is the universe (in the sense of a model, i.e., an interpretation, that is, semantics) in the sense of Model Theory), and correspondence (the interpretation function in the sense of Model Theory) of the values with the syntactical symbols, guided by a given lattice of truth values (evaluations), all this then changing à la Kripke except much faster.
I emphasize that I understand that the true situation is likely not to be able to be fit into either one of these characterizations, but I present it as a start from which a knowledgeable person may start a rough explanation (without quoting lines of code).
Thanks.
(a) the coded sensor data provides constant values for variables in the logic, so that the whole thing remains purely syntactical, with truth predicates either implicit or explicit, or
(b) the sensor data is the universe (in the sense of a model, i.e., an interpretation, that is, semantics) in the sense of Model Theory), and correspondence (the interpretation function in the sense of Model Theory) of the values with the syntactical symbols, guided by a given lattice of truth values (evaluations), all this then changing à la Kripke except much faster.
I emphasize that I understand that the true situation is likely not to be able to be fit into either one of these characterizations, but I present it as a start from which a knowledgeable person may start a rough explanation (without quoting lines of code).
Thanks.