I find it amusing that so many people is skeptic about general AI, trying to come up with arguments that it will never happen, while at the same time we do not understand how our own intelligence work. Go figure out.
There are more examples as well, as another user has commented, we didn't know what fire is until relatively recently but we have been using it for thousands of years.
But either way, is knowing the electron knowing electricity? There are so many properties of it that can be known and manipulated without that insight- and indeed they built up that understanding to reach practical engineering and use of electricity. That’s what I think is being gotten at wrt intelligence.
“Knowing” something isn’t necessarily about being aware of its smaller parts.
The source you linked already cites it as the first arc lamp.
> But either way, is knowing the electron knowing electricity? There are so many properties of it that can be known and manipulated without that insight- and indeed they built up that understanding to reach practical engineering and use of electricity. That’s what I think is being gotten at wrt intelligence.
Yes. That is exactly my point. We don't need to entirely understand what intelligence is in order to be able to create it. The same way we didn't know what fire is, but we created it with no problem.
But we can hardly define intelligence, let alone “entirely understand” it. A child could give a good , practical definition of fire and manipulate it skillfully thousands of years ago. Not so much us grown adults wrt intelligence today.
With fire, even “when things turn from themselves to ashes and produce heat” (which I imagine a prehistoric child could come up with) distinguishes fire usefully from most other phenomena in the world
Insane to me is to affirm that something has a limit when you don’t fully understand it.
And I think it’s a shame we haven’t considered what the limits are on “intelligence” very much. Knowing them has been immeasurably valuable in software engineering and algorithms, for one.
We can find plenty of examples where engineering advanced beyond our understanding: bridges, boats, tables, etc. When humanity started building those we didn’t have the full picture of our physics yet we build and used those for more than 1000s years.
Again, I’m not saying we can’t engineer something from knowledge, I’m saying we can’t affirm limits onto something we don’t fully understand yet.
IMHO this paper is speculative and biased towards our human intelligence. From all the advances I have seen so far in the AI landscape, I’m growing more and more skeptic that our intelligence is something so complex that we can’t replicate.
Grog: “Grog rubs two sticks together” Lowers voice and looks around furtively “really hard.”
So, I don’t see why rubbing these statistical model sticks should suddenly burst into intelligence, but I’m open to seeing convincing reasoning on that at some point. I wouldn’t invest time or energy in the meantime and like that original poster, think it’s kinda insane to if my goal was to see human-like intelligence emerge outside of humans
It also seems very odd that you can differentiate between some things that you think are intelligent, and some things that you think definitely are not, yet you are incapable of extracting any sort of goal from that knowledge.
If you could tell us your criteria, perhaps we could help you with that...
In these comments, when I’ve talked about an intelligence I can distinguish, I’ve been talking about human / animal intelligence. AGI implies an intelligence independent of that, so I’m asking about the specifics there - what are we calling intelligence if not “what humans do”?
If we are calling it just that, then I’d argue everything I know about how these models do things is very different from what I know of how humans approach the specific tasks the models are built against. And I’ve read that that’s intentional. So, even with that sort of definition I don’t see how it follows that these approaches are on any linear path to AGI (maybe nonlinear if we learn limits and such from mistakes).
I’ve since read more of the article (it’s long, huh?) I like the framework they use from Roitblat in Section 2 - and again, don’t see how LLMs and such are on the road to fulfilling those criteria.
I have a different idea of what AGI means: in my view, it is a retronym created in the 1980s in order to refer to AI of the sort Turing envisioned (which was more or less "what humans do") and differentiate it from things that were then being called AI, such as IBM's Deep Blue, which were mostly brute force applied to conceptually narrow problems.
You mentioned Roitblat's framework, and I would draw your attention to one aspect of it: it is not just a list of things that humans do, but those things which humans do considerably better than other animals, yet for all of them, there are other species that do them to some extent. As an evolutionist, I suppose there was a relatively recent time in the past when some of our ancestors or sibling species (all now extinct) had some or all of these skills to some intermediate level. In this view, intelligence is not an all-or-nothing concept, and achieving some of it is still progress.
Here's a view which you may not have seen: the pace of progress in AGI has not been constrained by an inability to define what we want, but by the pace at which we see ways to make what we see we need. For example, it is clear that current LLMs have a problem with truth, but it is not clear from what has been made public so far that anyone has a solution. Some people think that what's being done now with LLMs, but more of it, will be enough to get us to what will be generally accepted as AGI; I am skeptical, but I am willing to be persuaded otherwise if the evidence warrants it.
Fire is warm and it produces light, and it's easily observable in nature, it's a "thing" which humans could easily describe and recognize, before reproducing it. Someone was rubbing two sticks together, and noticed things became warmer, and warmer as they went, starting to feel like the warmth of fire and it happened.
In the case of AGI, I don't feel like we have a definition of done, so it seems kind of crazy to be chasing it / throwing money at it.
I didn't say say I'm against it, but does seem like a crazy way to go about it. Keep producing models that one day might mimic intelligence as we know it?
We are even able to predict whether other compounds might work without knowing why just based on structural similarity.
It’s ideal to know the full mechanism and it obviously aids engineering but there’s no reason you have to wait for that to use something. People used fire for millennia before oxidation reduction reactions were understood.
Seems a bit circular.
"What's a good definition of intelligence?" "Human intelligence." "What's human intelligence?" "What we want AI intelligence to be like."
No one in the planet would know how to be sure it's not just emulating human behavior.
Note that this is not an argument that it is possible, which certainly has not been conclusively established.