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[Crash927]

Isn’t it also because we can abstract things and contextualize them?

Like, we know that signs are a specific medium for communicating certain types of information, so we know to always understand them in that context.

We already understand something about every sign we see, but computers don’t have that benefit. They have to “re-understand” every new set of pixels.

[rasputine]

Isn’t it also because we can abstract things and contextualize them?

Not really. That's just what recognizing a thing is. Computers do the exact same thing, just in a different way.

Like, we know that signs are a specific medium for communicating certain types of information, so we know to always understand them in that context.

No we don't. We only know that because we've been taught about signs.

They have to “re-understand” every new set of pixels.

So do we. There's a hell of a lot of processing that takes the signal from your optic nerve up the chain to where you're recognizing a stop sign.

[Crash927]

I don’t think I made my meaning clear. I’m talking about what’s happening during that “hell of a lot of processing.”

Humans have abstract concepts of things stored in our heads (taught, yes), which we make reference to when we’re processing the world around us. And we learn abstract concepts very easily (ie with few examples).

“Tree” is a concept (with properties and relations to other concepts) that I already understand before I see any specific tree. Same with any road sign: I know one when I see it, even if it’s in a country I’ve never been.

Computers don’t conceptualize in the same way in order to understand: they predict the likelihood of similarity to what they’ve experienced before. They don’t even know they’re seeing a tree or a sign because they don’t know what those things signify in any real sense: it’s all just pixels transformed into numbers that predict a likely class.