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footurist t1_ivz26ai wrote

Reply to comment by AdditionalPizza in 2023: The year of Proto-AGI? by AdditionalPizza

The inadequacy occurs with the usage of the term prototype, which has a reasonably well defined meaning. Basically it serves as an MVP for one or more concepts that are themselves well-defined, so their feasibility and worthiness can be displayed. In the case at hand the concept is true generality of learning as we know it, which the current mainstream paradigm is definitively not capable of. As mentioned before, they might achieve limited imitation thereof, to an extent which is probably quite hard to guesstimate, but never the real thing ( in their current form, evolution can always change the landscape of course, but then they wouldn't be the same thing anymore ).

I recommend some YouTube videos by Numenta. Jeff Hawkins can explain these kinds of things to laymen incredibly well ( he was on Lex's podcast aswell ).

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AdditionalPizza OP t1_iw00jyx wrote

Your definition of prototype is not the full definition of the word though. Prototype can simply be the inspiration for later models. As in, we're on the right track and probably only adjustments/tweaking/fine-tuning, compute, and data away from being able to create full AGI. I think memory is a hurdle we will over come shortly.

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footurist t1_iw01b6x wrote

It is, in the sense that it must prove the concept. If it doesn't, it's maybe a precursor of some kind, but not the prototype.

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AdditionalPizza OP t1_iw02859 wrote

I'm saying 2023 the concept will be proven, we will see a concrete roadmap toward AGI because of the success that SOTA models will achieve.

But I think our very slight difference in 2 basically synonymous words is more pedantic than I feel like debating haha. Precursor and prototype are so similar I see no reason to argue either way.

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AsheyDS t1_iw0vwj7 wrote

Similar in your estimation. I'm guessing you don't work in a technical field. Proto-AGI is just not a good term and is wildly misleading to the general public and enthusiasts alike, and you're not doing anyone any favors by propagating it. You yourself are a victim of it's effects. All it does is create the sense that we're almost there, and that the current architectures are sufficient for AGI, and that any outstanding 'problems' aren't really problems anymore. That's nothing but pure speculation. We're not even sure if current transformers are on the same spectrum of classification as AGI. Who's to say it's a linear path? Narrow AI, even an interoperable collection of them, may yet hit a wall in terms of capability, and may not be the way forward. We just don't know yet. Nobody is stopping you from speculating, but using this term is highly inaccurate.

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AdditionalPizza OP t1_iw1b3ou wrote

And people in technical fields aren't notoriously awful at predicting what's best for the general public.

I'm not doing anyone any disservice, and not propogating anything negative here. My post is literally a poll asking people's opinion, and stating my own.

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