undefined | Better HN

0 pointsAlas16y ago0 comments

I see your point, but you're simply contesting the definition of intelligence that I assumed we were operating with, which is humanlike intelligence. Regardless of its extent, I think we would agree that intelligent behavior is consistent. My main point is that the current way we evaluate the artificial agents is not emphasizing their inconsistency.

Wikipedia defines Turing test as "a test of a machine's ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human". If we want to consider chimps intelligent, then in that context the definition of the Turing test should be adjusted accordingly. My point still stands: if we want to determine whether a chimp exhibits intelligence comparable to a human, we do the original Turing test. If we want to determine whether a chimp exhibits chimplike intelligence, we test not for, say, natural language but for whatever we want our definition of intelligence to include. If we want to determine whether an artificial agent has chimplike intelligence, we do the second Turing test. Unless the agent can display as consistent an intelligence as chimps, we shouldn't conclude that it's intelligent.

Regarding your point on weak measures: If I can find an endless stream of cases of failure with respect to a measure that we care about improving, then whatever collation of weak measures we had should be null. Wouldn't you agree? I'm not against using weak measures to detect intelligence, but only as long as it's not trivial to generate failures. If a chimp displays an ability for abstract reasoning when I'm observing it in a cage but suddenly loses this ability once set free in a forest, it's not intelligent.

0 comments

3 comments · 1 top-level

Veedrac6y ago· 2 in thread

I'm not interested in categorizing for the sake of categorizing, I'm interested in how AI researchers and those otherwise involved can get a measure of where they're at and where they can expect to be.

If AI researchers were growing neurons in vats and those neurons were displaying abilities on par with chimpanzees I'd want those researchers to be able to say ‘hold up, we might be getting close to par-human intelligence, let's make sure we do this right.’ And I want them to be able to do that even though their brains in vats can't pass a Turing test or write bad poetry or play basic Atari games and the naysayers around them continue to mock them for worrying when their brains in vats can't even pass a Turing test or write bad poetry or play basic Atari games.

Like, I don't particularly care that AI can't solve or even approach solving the Turing test now, because I already know it isn't human-par intelligent, and more data pointing that out tells me nothing about where we are and what's out of reach. All we really know is that we've been doing the real empirical work with fast computers for 20ish years now and gone from no results to many incredible results, and in the next 30 years our models are going to get vastly more sophisticated and probably four orders of magnitude larger.

Where does this end up? I don't know, but dismissing our measures of progress and improved generality with ‘nowhere near as robust as [...] humans’ is certainly not the way figure it out.

> If I can find an endless stream of cases of failure with respect to a measure that we care about improving, then whatever collation of weak measures we had should be null. Wouldn't you agree?

No? Isn't this obviously false? People can't multiply thousand-digit numbers in their heads; why should that in any way invalidate their other measures of intelligence?

Alas1OP6y ago

>no results to many incredible results

What exactly is incredible (relatively) about the current state of things? I don't know how up-to-date you are on research, but how can you be claiming that we had no results previously? This is the kind of ignorance of previous work that we should be avoiding. We had the same kind of results previously, only with lower numbers. I keep trying to explain that increasing the numbers is not going to get us there because the numbers are measuring the wrong thing. There are other things that we should also focus on improving.

>dismissing our measures of progress and improved generality with ‘nowhere near as robust as [...] humans’ is certainly not the way figure it out.

It is the way to save this field from wasting so much money and time on coming up with the next small tweak to get that 0.001 improvement in whatever number you're trying to increase. It is not a naive or spiteful dismissal of the measures, it is a critique of the measures since they should not be the primary goal. The majority of this community is mindlessly tweaking architectures in pursuit of publications. Standards of publication should be higher to discourage this kind of behavior. With this much money and manpower, it should be exploding in orthogonal directions instead. But that requires taste and vision, which are unfortunately rare.

>People can't multiply thousand-digit numbers in their heads; why should that in any way invalidate their other measures of intelligence?

Is rote multiplication a task that we're interested in achieving with AI? You say that you aren't interested categorizing for the sake of categorizing, but this is a counterexample for the sake of giving a counterexample. Avoiding this kind of an example is precisely why I said "a measure that we care about improving".

Veedrac6y ago

> What exactly is incredible (relatively) about the current state of things?

Compared to 1999?

Watch https://www.youtube.com/watch?v=kSLJriaOumA

Hear https://audio-samples.github.io/#section-4

Read https://grover.allenai.org/

These are not just ‘increasing numbers’. These are fucking witchcraft, and if we didn't live in a world with 5 inch blocks of magical silicon that talk to us and giant tubes of aluminium that fly in the sky the average person would still have the sense to recognize it.

> It is the way to save this field from [...]

For us to have a productive conversation here you need to either respond to my criticisms of this line of argument or accept that it's wrong. Being disingenuous because you like what the argument would encourage if it were true doesn't help when your argument isn't true.

> Is rote multiplication a task that we're interested in achieving with AI?

It's a measure for which improvement would have meaningful positive impact on our ability to reason, so it's a measure we should wish to improve all else equal. Yes, it's marginal, yes, it's silly, that's the point: failure in one corner does not equate to failure in them all.

1 more reply

j / k navigate · click thread line to collapse