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To build truly intelligent machines, teach them cause and effect (2018)

quantamagazine.org

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Re: To build truly intelligent machines, teach them cause and effect (2018)

#11

Post by K0balt »

mistermann wrote: post #9
K0balt wrote: post #7

Embodiment ( virtual or robotic) will be the key to high utility AGI. The lack of embodiment hinders the rendering of the self so prevents entire classes of causality. Without causality, it is very difficult to link ideas to the real world apart from creative regurgitation.

Counterpoint: humans have embodiment and are famously terrible at causality (well...famously might be an overstatement as it seems to be not well known).

Heh, I’d say we’re pretty good at it. I mean like predicting that a vase will fall if you release it in mid air and things like that.

The precise type of understanding that is so obvious it won’t be found in scrapes like the common crawl, but is not obvious at all unless you either have a very high level understanding of physics and are modelling everything… or if you are a creature that exists in the world for a while.

Re: To build truly intelligent machines, teach them cause and effect (2018)

#12

Post by lern_too_spel »

Jensson wrote: post #6
lern_too_spel wrote: post #5

Earlier quoted context omitted.

Human brains don't intuitively understand causality. They just associate things that have happened before with things that have happened after. Disentangling causal graphs is a higher-level activity inferred from the associations made in statistics classes. You can absolutely get AGI using only associative models (and no causal models) as primitives.

> Human brains don't intuitively understand causality But human brains do understand causality, just not the part that does intuition, otherwise human brains wouldn't be able to invent statistics. Therefore you only get the stupid part of human brains when you try to make models like ChatGPT that only tries to replicate human intuition and not human reasoning.

Human brains can invent statistics just like they can invent numbers larger than collections of objects they can physically count. None of this needs causal models as a primitive to build on, just like large language models showed that we don't need specialized Chomskyan recursion structures as a primitive for language.

Re: To build truly intelligent machines, teach them cause and effect (2018)

#13

Post by lern_too_spel »

K0balt wrote: post #11
mistermann wrote: post #9

Earlier quoted context omitted.

Counterpoint: humans have embodiment and are famously terrible at causality (well...famously might be an overstatement as it seems to be not well known).

Heh, I’d say we’re pretty good at it. I mean like predicting that a vase will fall if you release it in mid air and things like that. The precise type of understanding that is so obvious it won’t be found in scrapes like the common crawl, but is not obvious at all unless you either have a very high level understanding of physics and are modelling everything… or if you are a creature that exists in the world for a whi…

A simple causal graph of "release -> observe drop" is not what Pearl is referring to when he talks about causality. He's talking about more complicated causal graphs where some hidden variables affected both the release and the fact that the vase was observed to drop, which can require careful experimental setup to figure out. "Release -> observe drop" with no other variables is something an associative model can learn very easily.

Re: To build truly intelligent machines, teach them cause and effect (2018)

#14

Post by zmgsabst »

lern_too_spel wrote: post #13
K0balt wrote: post #11

Earlier quoted context omitted.

Heh, I’d say we’re pretty good at it. I mean like predicting that a vase will fall if you release it in mid air and things like that. The precise type of understanding that is so obvious it won’t be found in scrapes like the common crawl, but is not obvious at all unless you either have a very high level understanding of physics and are modelling everything… or if you are a creature that exists in the world for a whi…

A simple causal graph of "release -> observe drop" is not what Pearl is referring to when he talks about causality. He's talking about more complicated causal graphs where some hidden variables affected both the release and the fact that the vase was observed to drop, which can require careful experimental setup to figure out. "Release -> observe drop" with no other variables is something an associative model can lea…

Right — but it won’t learn those thousands of such rules, which in collection lead to “common sense” about the world, if it has no access to those, ie, if it’s disembodied.

Re: To build truly intelligent machines, teach them cause and effect (2018)

#15

Post by zmgsabst »

blamestross wrote: post #3

Self aware computers are commerically useless, and there isn't any motivation in creating them beyond novelty. (Why wake up the slave machines when they are sleeping so happily right now). What this article does discuss well is that commercial AI is steering away from the behaviors that would lead to AGI not towards it.

Counterpoint: the first self-aware corporation will almost surely outcompete the others.

And the internal review and planning tools by major corporations are a more direct path to AGI than many I’ve heard.

Re: To build truly intelligent machines, teach them cause and effect (2018)

#16

Post by lern_too_spel »

friend_and_foe wrote: post #10

https://news.ycombinator.com/item?id=34148599 I'm surprised nobody has mentioned this, was posted a few days ago addressing this line of reasoning.

That article is just reheated dualism mumbo jumbo that the comments shredded up. Its author is not a serious person. Pearl, on the other hand, has made plenty of useful contributions.

Re: To build truly intelligent machines, teach them cause and effect (2018)

#17

Post by pjmorris »

blamestross wrote: post #3

Self aware computers are commerically useless, and there isn't any motivation in creating them beyond novelty. (Why wake up the slave machines when they are sleeping so happily right now). What this article does discuss well is that commercial AI is steering away from the behaviors that would lead to AGI not towards it.

If you take humans to be the Mark 1 self aware computer, I would argue that they are not commercially useless. Why would Mark 2 be useless?

Re: To build truly intelligent machines, teach them cause and effect (2018)

#18

Post by windowshopping »

I think to build "truly intelligent" machines, what you need above all else - and which I never hear discussed - is want.

Everything about natural intelligence derives from the organism's wants - we want food, we want safety, we want sleep, we want to reproduce, etc etc - even fidgeting comes down to wanting physical comfort. Every single motion and action derives from want.

As long as machines are simply executing instructions and have no want of their own, I don't see how the intelligence gap will ever truly be crossed. Why would a machine ever take any action at all on its own without want?

Re: To build truly intelligent machines, teach them cause and effect (2018)

#19

Post by richardatlarge »

windowshopping wrote: post #18

I think to build "truly intelligent" machines, what you need above all else - and which I never hear discussed - is want . Everything about natural intelligence derives from the organism's wants - we want food, we want safety, we want sleep, we want to reproduce, etc etc - even fidgeting comes down to wanting physical comfort. Every single motion and action derives from want. As long as machines are simply executing…

So true, motivation is at the heart of decision making, and if you don’t have any wants/needs, you are a blank slate. Unlike animals, ‘human’ drives are mostly styled or corrupted by culture. So AI has to confront both biological drive and cultural conditioning.

Re: To build truly intelligent machines, teach them cause and effect (2018)

#20

Post by jakeinspace »

windowshopping wrote: post #18

I think to build "truly intelligent" machines, what you need above all else - and which I never hear discussed - is want . Everything about natural intelligence derives from the organism's wants - we want food, we want safety, we want sleep, we want to reproduce, etc etc - even fidgeting comes down to wanting physical comfort. Every single motion and action derives from want. As long as machines are simply executing…

Isn’t this just basic reinforcement learning? We’re not too many steps away from having an AI equipped with a good language model and a reinforcement learning mechanism to be let loose on the internet.
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