And I don't just mean this from the old point of view of "if we understand it, it's not AI anymore", I mean, the model has serious fundamental limitations. One of them is that it's static, so, once trained, it doesn't learn from its future input. Another is that when it is doing its "what is the highest probability text output to follow this text" (which, itself, is not exactly the sort of question "Strong AI" is the answer to), it by construction can only use a fixed-size window of text. So, for instance, it is by construction simply impossible for GPT-3 to write a novel, or even a short story, because the only way to get it to keep outputting is to provide it a window of the last X KB of output (I don't recall exactly how big it is) for the next continuation, which means that as it is writing the X+5th KB of output, it has literally completely forgotten the first 5KB of output, as completely as if it never existed.
On the flip side, it is clearly very interesting and there is something there. However, I'd submit that what that something is is a something that we don't have an English word for, because up to this point humanity has never encountered anything with a cognitive model like GPT-3. So, it doesn't have "understanding", it has a quality-that-has-no-name (not to be confused with the "quality without a name" which GPT-3 most certainly does not have yet).
There is indeed. I'll recount my own words after my first proper exposure to the model, in the form of playing custom stories in AI Dungeon:
"I played more of it today, and I can confirm that prolonged exposure makes me feel like I'm half awake, and half in a dream - particularly when the real world interrupts, I feel like I didn't fully wake up.
What's worse, whenever I tried to talk to a real person today, I've felt like I'm just feeding words to an AI, and anticipated "story" to evolve.
Never before has a game messed up with my mind so badly. I'm not sure if it's safe."
To which I got a reply perfectly summarizing the phenomenon:
"AI Dungeon feels a bit like a fever-dream."
--
It's been a year since; thinking back, I feel the trick here is, GPT-3 crosses the threshold of being able to produce plausible and interesting text - where by "interesting" I mean "almost, but not quite, unpredictable". The way other people and their stories are interesting - their words aren't totally random, you have this feeling for the possible trajectories the conversation can take, but you can't quite guess what they're going to say next. GPT-3 does that well enough that it's easy to suspend disbelief and feel as if you're dealing with a mind. But then the feelings that arise in you, that's just you projecting - engaging your mental machinery for dealing with other minds.
I did play with AI dungeon, and I would say the analogy to a dream is even deeper than it may appear at first, because I found that lucid dreaming techniques basically work on it, which is bizarrely impressive. I would characterize a lot of what one does in lucid dreaming (or, at least, what I do) is basically "expectations management"; if you can learn to expect something to happen in a dream, it frequently does. Not necessarily exactly what you "expected", but it will have a very significant influence. Correspondingly, it is possible (and indeed easy) to basically lead the AI along by using your text prompts to expect things to happen, and in a very dreamlike fashion, while that doesn't mean the exact thing you "expected" will be what the AI produces, it can clearly have very very significant impact on the result.
I should warn you this sort of removes the magic from AI Dungeon as an experience though... I have to consciously "let" it drive the story because it's pretty easy to exert much more control than you're "supposed" to have, when you know how to look behind the curtain.
I think that terms like "philosophical zombie" may be close to the truth, but I'm guessing some sci-fi work has a term that we could adopt.
But the quote doesn't say that GPT-3 can't produce understanding because of the specifics of how it works, but "because understanding cannot occur in an isolated computation or behavior, no matter how clever", which is a more general claim.
I don't have to be able nail down exactly what kind of state change "understanding" is to point out that the way we use the word clearly entails one, and GPT-3 clearly can't have one, so therefore it is quite reasonably excluded from "understanding".
(In theory GPT-3 could be extended by continuous online training, but my impression is that convergence is too slow for that to be practical, and it wouldn't look much like "learning".)
There are plenty of things that can't (or can't efficiently) be represented in a single agent.
This is (for example) Hayek's main critique of central planning: "[price] understanding cannot occur in an isolated computation or behavior"; there are simply too many necessary details to fit into any one head/computer, and therefore we should prefer markets. (Markets being definitionally not located in any one isolated computation/behavior, but inter-agentially in lots of them.)
If you simulate a body with the same inputs as the existing brain, do you just have a "faster horse" problem, where you have a brain that could possibly perceive/process information faster (or slower) than a real human depending on the speed of the simulation? That could be useful, but sounds potentially rather bleak, especially if we limit what it can do to change its environment. It also seems limited for e.g. central planning - it can do planning faster than any individual, but likely will still have working memory size limitations, if it's just a simulation of a human brain. So it may not be so much better than parallelizing tasks across a bunch of humans.
More interesting, probably, then, than the "super human" style, is giving a new sort of intelligence different and additional senses, so that it doesn't want or need the same sort of physical embodiment we have, a la the "set sets" in the Terra Ignota series. But then we have to figure out what separates abstract intelligence from our own senses, and how to usefully augment it with new senses for a data-based world...
Purpose doesn't automatically mean civilized, but you can't get to civilized without purpose. It's an okay word to use for outlining what's missing.
AI output is increasingly coherent but MEANINGLESS. If you want to look to meaning and purpose, a better place to look might be emergent behaviors of the YouTube Algorithm, or Facebook feed.
Those can easily take toxic swings because they're operating in the absence of a higher sense of what will happen: they're the consciousness of a worm or insect. But they show purpose, where the more coherent and intelligence-like outputs of GPT-3 keep on betraying a lack of meaning.
GPT-3 doesn't WANT anything. There's the problem (though at this stage I think it's just as well). Only that will bring real AI… which can be a daunting prospect.
Some of us here despise the writing style of The New Yorker. The writing is beautiful, literary, but it takes it forever to say anything. GPT-3 is like that, but worse, because it has nothing to say.
If you align what minimizing train error means with a larger purpose, it will seemingly make magic happen.
Just like you, online, trying to figure out how to turn this into copulatory success. It doesn’t matter if you succeed but don’t understand why, only that you succeed.
It will be HUNGRY in the way GPT-3 is not: through both indirect and direct pressures, it will be struggling to maximize engagement, reach more places, get more food in the sense of people trying to interact with it.
The Facebook news feed, and even more so the less human-centered algorithms of Google and YouTube, are more conscious than GPT-3. When they're adjusted, such as the times Google has fiddled with the algorithm because YouTube was pipelining people to the alt-right after it 'observed' that this heightened engagement a lot, the algorithms are adjusted by trying to give them other types of information, other priorities (like giving them more sensory organs to highlight stuff they'd missed about their larger environment) rather than by diving in and recoding specifica about particular youtube creators, or looking for a more narrowly defined 'politics' that had been coded in there.
No such nefarious coding existed. The algorithm is alive, but blind. It functions on a scale where it can't NOT trample its surroundings, so it must be given eyes… and the consciousness gradually increases.
A well-known example are the ants: individual ants are somewhat dumb, barely above simple chemical seekers. But the ant colony behaves as a single organism, and quite smart at that.
Other examples include cities, nations, corporations - it kind of feels like these organizations have minds of their own, with individual humans being cells, and the bureaucracy forming a computational substrate.
In the same vein, Facebook feed could be seen as a mind of its own. So could the entire human civilization.
As for humans losing the ability to understand - that does sound a little bit panicky.
Ah, right, it won't work because it doesn't have a soul. Got it.