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FrameBenignly comments on Open Thread, January 4-10, 2016 - Less Wrong Discussion
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Lessons from teaching a neural network...
Grandma teaches our baby that a pink toy cat is "meow".
Baby calls the pink cat "meow".
Parents celebrate. (It's her first word!)
Later Barbara notices that the baby also calls another pink toy non-cat "meow".
The celebration stops; the parents are concerned.
Viliam: "We need to teach her that this other pink toy is... uhm... actually, what is this thing? Is that a pig or a pink bear or what? I have no idea. Why do people create such horribly unrealistic toys for the innocent little children?"
Barbara shrugs.
Viliam: "I guess if we don't know, it's okay if the baby doesn't know either. The toys are kinda similar. Let's ignore this, so we neither correct her nor reward her for calling this toy 'meow'."
Barbara: "I noticed that the baby also calls the pink fish 'meow'."
Viliam: "Okay... I think now the problem is obvious... and so is the solution."
Viliam brings a white toy cat and teaches the baby that this toy is also "meow".
Baby initially seems incredulous, but gradually accepts.
A week later, the baby calls every toy and grandma "meow".
So the child was generalizing along the wrong dimension, so you decided the solution was to train an increase in generalization of the word meow which is what you got. You need to teach discrimination; not generalization. A method for doing so is to present the pink cat and pink fish sequentially. Reward the meow response in the presence of the cat, and reward fish responses to the fish. Eventually meow responses to the fish should extinguish.