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Probabilistic AI can't be AI

refaktorlabs.blogspot.com

11–20 of 32 posts

Re: Probabilistic AI can't be AI

#11
- SVMs aren't really probabilistic models. They don't need to be thought of in a way that assumes underlying statistical properties of what they're measuring. Many machine learning methods (decision trees for one) are similarly agnostic.

- Reality is a probabilistic process. Brains work probabilistically at least in the sense that the underlying biomechanics have some statistical distribution.

I have the feeling the author doesn't really understand what "probability" means, as he more or less admits.

Re: Probabilistic AI can't be AI

#12
First off, the title is terribly imprecise, you're not arguing that probabilistic AI can't be AI, you're arguing that animal intelligence is not probabilistic.

Second off, I personally find your theses unconvincing because the simple statements are easily refuted, and there's not enough supporting information to make them into tighter arguments.

For example, for your first bullet point, the underlying mechanism could be highly probabilistic, without our consciousness having access to the probabilities as they are executed. We do not have conscious knowledge of neuron potentials, or of any other internal state of the physical mechanisms of our consciousness, but that does not mean that they don't exist.

Further, people are bad at reasoning period, and have to be taught how to do it in school. It's only through much training that we learn reasoning from certainties, and reasoning with uncertainty will similarly require training.

Finally, I don't think that anybody is saying that our brains operate SVMs or RBMs or anything like that, they are merely computational mechanisms to replicate the behavior of complex networks of neurons; there may be direct analogs to computation in how neurons integrate chemical, electrical, and epigenetic signals, but it's not clear that they're exactly the same thing; and that doesn't mean that even if it's completely different, that a probabilistic AI can't be an Intelligence.

These are heady matters that people put a lot of careful thought into, and while there's definitely room for light discussion among friends, I'm not sure that this is the right material for HN.

Re: Probabilistic AI can't be AI

#13
post #6

This article is deeply flawed. First of all, it's premise is flawed; secondly, it's supporting evidence is flawed. Example from supporting evidence: "then people would be naturally great at probability, and we know we suck at probability" No, this does not follow at all. There is absolutely no reason to assume that a probabilistic algorithm would somehow lead to better results when dealing with probabilities at a muc…

so you think that we use probability (and are good at it) on a low level but that doesn't translate to being sufficient in probability on a higher level. Where is the border between low and high?

I am not saying any probabilistic intelligence can't work. Please define any "intelligence" or link to definition. I said I think "we" or organic intelligence doesn't with use of probability.

I am also not saying probabilistic models are useless / bad / or not worth exploring further for making better programs or anything, I just don't think human intelligence uses them as a basis.

Re: Probabilistic AI can't be AI

#14
post #5

The problem with this assumption is that one doesn't have to be aware of how their own brains work in order for them to work. The fact that people seem to be universally bad at assessing probabilities means only that however their brains work, that mechanism doesn't produce intelligences that are finely adapted at assessing probabilities. The machinery that is producing that intelligence could still be completely pro…

We can't say that humans are fantastic at pattern recognition either. We may only be sure that our built-in pattern recognition is better than our ability to create pattern recognition algorithms.

Re: Probabilistic AI can't be AI

#15

First off, the title is terribly imprecise, you're not arguing that probabilistic AI can't be AI, you're arguing that animal intelligence is not probabilistic. Second off, I personally find your theses unconvincing because the simple statements are easily refuted, and there's not enough supporting information to make them into tighter arguments. For example, for your first bullet point, the underlying mechanism could…

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Re: Probabilistic AI can't be AI

#16
The argument itself is flawed as pointed out by others.

As for the subject of probabilistic AI there's quite a lot of evidence that natural language grammar to a large extent is probabilistic. In fact I'd say that most natural language grammar rules are just surface representations of probabilistic models such as Hidden Markov models.

Re: Probabilistic AI can't be AI

#17

First off, the title is terribly imprecise, you're not arguing that probabilistic AI can't be AI, you're arguing that animal intelligence is not probabilistic. Second off, I personally find your theses unconvincing because the simple statements are easily refuted, and there's not enough supporting information to make them into tighter arguments. For example, for your first bullet point, the underlying mechanism could…

you are right about the title, sorry.

is there a consensus/definition on what is AI without relying on what animal/human intell. looks like/functions?

Re: Probabilistic AI can't be AI

#18
The argument is fundamentally and fatally flawed by a lack of understanding of how the "mind" works.

The basic flaw in the argument is that there is only one "mind" and that all its workings are available to us.

But as much recent research shows, especially that of Tversky and Kahneman, we have at least two "minds", the so-called "fast" and "slow" systems, and the "fast" system is not directly accessible to "us" - and "us", what we recognize as "us", is the working of "slow", the deliberate, conscious, effortful problem solver, often called upon to cook up a "good enough story" to explain an exception "fast" couldn't make sense of.

"Fast" might be terrifically good at probability, with some survival heuristics favouring particular conclusions - better to always conclude that those weird pattens in the bush are a tiger than to be wrong once.

Since "fast" is not really accessible to "slow", it matters not how good "fast" is at probability - and "fast" could be 100% probabilistic AI and we'd never know it...

...not without detailed neurophychological study, at least. It certainly wouldn't "just be evident".

Re: Probabilistic AI can't be AI

#19
then people would be naturally great at probability

Where do you get that conclusion? Think of a baseball player with exceptional hand-eye coordination, who also knows absolutely nothing about any of the math or calculus behind it. There is a vast chasm between conscious and subconscious thought (where the latter might be viewed as the underlying "intelligence model"). I don't agree that a (partially) probabilistic model would necessarily imply a proficiency at the conscious, communicable level.

we wouldn't benefit from learning about and consciously using probability to solve problems, as our brain would already do it on a lower level.

Don't understand this one either. Back to the baseball player - there is a lot of value we gain from our brains "naturally" solving e.g. inverse kinematics problems on the fly. But, there is also a lot we gain from understanding these mathematical concepts at the conscious level. Totally different realms, both useful.

Statistical methods generally need a big learning set to learn anything.

Ok, that's a limitation of the current AI models. They're not smart enough to infer the essential characteristics of an elephant from a small set (it's also a very narrow approach...you don't start a child off by showing them pictures of elephants, first they have to spend a long time acquiring basic fundamentals of knowledge and perception). I don't see how that implies a more deterministic nature of organic intelligence.

Even the child might think something is an elephant and be wrong. But (IMO) it's the same process of using the bits of knowledge you have to make a guess (and an estimated degree of certainty). "It could be this thing or it could be that thing, and my model says it has the greatest probability of being this one, so that's what I'm going with."

Re: Probabilistic AI can't be AI

#20

then people would be naturally great at probability Where do you get that conclusion? Think of a baseball player with exceptional hand-eye coordination, who also knows absolutely nothing about any of the math or calculus behind it. There is a vast chasm between conscious and subconscious thought (where the latter might be viewed as the underlying "intelligence model"). I don't agree that a (partially) probabilistic m…

but the baseball player with exceptional h-e coordination would catch the ball without learning about math or calculus behind it. We suck at probabilities naturally / don't catch the ball naturally.

Otherwise I agree with what you said (and am limited in time, sorry)

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