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Probabilistic AI can't be AI

refaktorlabs.blogspot.com

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Re: Probabilistic AI can't be AI

#21

Post by Houshalter »

I originally intended to make a comment about how wrong this is because almost all approaches to AI and ML are deeply rooted in probability and statistics. The entire problem of intelligence is based on making accurate predictions and then acting on them. But there is some truth in this. Humans are terrible at probability and that's something I wouldn't have expected if I didn't already know it. It is a clue as to what kind of algorithm the brain is using.

I still disagree that the brain doesn't use probability at all or that we shouldn't focus on it in AI research.

>There are more external signs that we don't do probability. Statistical methods generally need a big learning set to learn anything. A small child doesn't have to see a set of 500 cartoon elephants in different poses to recognize elephants from then on in various different cartoons and in real life *)

No but they do see hundreds of hours of visual feed from their eyes from which they learn high level features. Learning an elephant from one example wouldn't be possible without first learning thousands of other concepts such as how to detect edges, shapes, 3d objects, the properties of animals, etc.

Re: Probabilistic AI can't be AI

#22

Post by sieisteinmodel »

fiatmoney wrote: post #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…

> Brains work probabilistically at least in the sense that the underlying biomechanics have some statistical distribution.

No, it's us that use these distribution to model them. Reality might be deterministic after all (no proof of the contrary), and then brains are not working probabilistic at all.

Re: Probabilistic AI can't be AI

#23

Post by nabla9 »

middayc wrote: post #3
therobot24 wrote: post #2

TL;DR: "I'm not an AI/ML anything by any stretch of imagination"

good one, I accept it :) edit: so you think human intelligence is mainly a probability machine?

Something to read:

Hierarchical Bayesian Modeling of Human Decision-Making Using Wiener Diffusion http://gandalf.psych.umn.edu/users/schrater/schrater_lab/cou...

Decision Theory and Human Behavior http://www.umass.edu/preferen/Class%20Material/Bounds%20of%2...

Beyond Accuracy: How Models of Decision Making Compare to Human Decision Making http://fileadmin.cs.lth.se/cs/Personal/Carl_Christian_Rolf/c...

Forgetful Bayes and myopic planning: Human learning and decision-making in a bandit setting http://papers.nips.cc/paper/5180-forgetful-bayes-and-myopic-...

>Our result shows that subjects’ choices, on a trial-to- trial basis, are best captured by a “forgetful” Bayesian iterative learning model [21] in combination with a partially myopic decision policy known as Knowledge Gradient [7].

Re: Probabilistic AI can't be AI

#24

Post by wlievens »

middayc wrote: post #17
epistasis wrote: post #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…

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?

I offer one crude definition: intelligence is a requirement for an agent that can solve a wid range of problems, without being specifically designed for these problems.

Re: Probabilistic AI can't be AI

#25

Post by wlievens »

sieisteinmodel wrote: post #22
fiatmoney wrote: post #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…

> Brains work probabilistically at least in the sense that the underlying biomechanics have some statistical distribution. No, it's us that use these distribution to model them. Reality might be deterministic after all (no proof of the contrary), and then brains are not working probabilistic at all.

I would think even entirely deterministic systems need to be treated probabilistically if you don't have perfect information.

Re: Probabilistic AI can't be AI

#26

Post by aeorgnoieang »

resu_nimda wrote: post #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 m…

I stopped reading at that first point too.

Re: Probabilistic AI can't be AI

#27

Post by middayc »

PeterWhittaker wrote: post #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" - an…

My argument doesn't assume that we don't have unconscious processes. Maybe I didn't express well what I think. I do think we have multiple "minds" (I even wrote a blogpost on this subject on another blog once).

Maybe my "then people would be naturally great at probability" came out as if we would then consciously know about probability, know the formulas etc without the need to learn about them.

No. I tried to say that if so then results of our "fast" mind would be very well attuned to probabilistic study of the problem. For example, you wouldn't become scared when boarding a plane.

I will try to write another blogpost being more precise. Not that it's worth anything, more for myself. I won't post it here, not because of opposing comments, but because many think this is not a HN material and I don't want to spam.

Not that it matters, obviously. But I don't think there is no probability processing anywhere in the system (we do conscious probability if not else). My thoughts were that it can't be the main or important driver behind it all. I think the memory itself (storage and "soft" retrieval of information .. my theory on models that we make) plays much more important role in our function than any special or complex algorithm. Again, not that it matters what I think.

Re: Probabilistic AI can't be AI

#28

Post by middayc »

eamsen wrote: post #9

...people would be naturally great at probability, and we know we suck at probability Human bodies are based on molecules, it doesn't imply that people understand chemistry. Computer chips are based on transistors, it doesn't imply that computers understand electronics. Sorry, but your assumption that knowledge is inherited by foundations would imply that everything understands the Universe.

I see now that I probably didn't express myself well. I am not saying we should understand probability but the result of our instincts should be in tune with probabilistic results on the problem. For example: We would not naturally fear airplanes, terror, etc. or..

If human body is made from molecules it does mean that we function as blobs of molecules.

If computer chips are based on transistors, the output of computer chips is transistor like.

Re: Probabilistic AI can't be AI

#29

Post by middayc »

Houshalter wrote: post #21

I originally intended to make a comment about how wrong this is because almost all approaches to AI and ML are deeply rooted in probability and statistics. The entire problem of intelligence is based on making accurate predictions and then acting on them. But there is some truth in this. Humans are terrible at probability and that's something I wouldn't have expected if I didn't already know it. It is a clue as to wh…

I am not saying that it doesn't use something that efectively is a probability calculation anywhere in the system, but that that isn't the main or the most important "engine".

I agree with your comment on "first learning thousands of other concepts". But that is a ton of (hierarchical) concepts that have to bo stored somehow and isn't then the storage/retrieval itself maybe more cruicial to the whole function than any special algo we just haven't figured out yet? (I mention this in my "wild" speculation on "models") :)

Re: Probabilistic AI can't be AI

#30

Post by middayc »

Mikeb85 wrote: post #8

I disagree with some of the premises. We are great at probability, we compute it unconsciously. Every person knows the approximate probability of flipping a coin to show heads, pulling a card from a stack, or being rejected/successful when asking a date out (we always say our 'chances' are good/bad, depending on factors we think are important). In our day to day lives, many decisions are driven by what we think the '…

I am not sure if I intuitively know it or do we have to consciously compute / infer it? (the coin/card example).

I guess I have some aprox feeling, but it's highly susceptible to being skewed.

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