And you are right ![]()
It is. The ‘target’.
‘Modelling’…‘Checking’. Yup, precisely. I don’t see a computer model as a despicable end-product. It is an integral part of our R&D (or even theorization) toolbelt now, for modelling and checking. As much as a pen and paper for drawing boxes, arrows, and/or equations.
You do realize, that what I find the most interesting known-output of all, as far as V1 goes, is the output of the ‘learning’ function itself, right ?
aka the end-state of those cells and dendrites and synapses after exposition.
Assuming that you do… I don’t quite understand over what we’re disagreeing here.
- If you think V1 formation is so complicated that it won’t work in isolation, then we’ll try to add parts of a hierarchy. I stated as much already. That endeavor could give us some evidence of this very requirement.
- If you think V1 formation is so simple that any model would do, and thus we won’t get any insight reaching it, then… well at that point I don’t think it will be that easy. But right; it is some possible concern. If that turns out to be the case we can always turn the ‘probing’ part on its head and look for models which fail. Or strip ingredients one by one to get a clue about which are the necessary ones…
We’ll learn ‘something’ either way.
I don’t know how my coding skills are relevant to the discussion, since you did understand that I don’t want to hardcode V1-like output (or didn’t you ? the purpose is not a clever edge detector for the sake of it), but let a model learn online and see if its cells tune themselves towards edge detection and stuff.
Now, if your concern is that I can’t model anything before having a well-defined model in the first place, I’ll restate that ‘let a model learn online’ in the sentence above will more likely turn out to be an iterative ‘let several, many, theorized models, in turn, learn online’. And see which of these succeeds. I may already have some insights for the first tries, granted… but I’m not putting too much confidence in them anyway, and all these models (against which to “check the plausibility of your theoretical ideas”) could very well be dug out/refined/invented as we go.
‘Invented’… Hacker-style
since I’m no Einstein, sadly.
To conclude… I don’t know how V1 decision of forming ‘simple’ edge detection when exposed to visual stimulus is relevant to (A)GI. But I strongly bet that it is. Relevant. V1 is cortex. We both agreed on that, it seems. And I believe, that by witnessing concretely ‘how’ would V1 be driven to come to that particular choice, we’d gain insight into precisely that.
“What stands as relevant info and/or coincidences to wire to, from an (A)GI’s substrate point of view”.
Quite the nut to crack if you ask me.