> If you think about it, natural "intelligence" itself can be understood as another type of predictor: you build a world model to anticipate what will happen next so you can plan your actions accordingly and survive.

Yes.

Human intelligence consists of three things.

First, groundedness: The ability to form a representation of the world and one’s place in it.

Second, a temporal-spatial sense: A subjective and bounded idea of self in objective space and time.

Third: A general predictive function which is capable of broad abstraction.

At its most basic level, this third element enables man to acquire, process, store, represent, and continually re-acquire knowledge which is external to that man's subjective existence. This is calculation in the strictest sense.

And it is the third element -- the strength, speed, and breadth of the predictive function -- which is synonymous with the word "intelligence." Higher animals have all three elements, but they're pretty hazy -- especially the third. And, in humans, short time horizons are synonymous with intellectual dullness.

All of this is to say that if you have a "prediction machine" you're 90% of the way to a true "intelligence machine." It also, I think, suggests routes that might lead to more robust AI in the future. (Ground the AI, give it a limited physical presence in time and space, match its clocks to the outside world.)

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quonn 3 days ago | parent [-]

"Prediction" is hardly more than another term for inference. It's the very essence of machine learning. There is nothing new or useful in this concept.

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A_D_E_P_T 3 days ago | parent [-]

Point is that it's also exactly analogous to human intelligence. There's almost nothing else to it.

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devmor 3 days ago | parent [-]

This is how you spot hype nonsense - claims that anything is analogous to human intelligence. Even absent all other objections, we don't understand the human mind well enough to make a claim like that.

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A_D_E_P_T 3 days ago | parent [-]

You don't need to understand the human mind on a mechanistic level. You only need to examine how the whole organism learns, acts, and reacts to stimulus and situation.

Even something as simple as catching a ball is basically predictive. You predict where the ball will be along its arc when it reaches a point in space where you can catch it. Then, strictly informed by that prediction, you solve a problem of motion through space -- and some very simple-seeming problems of motion through space can't be cracked in a general case without a very powerful supercomputer -- to physically catch the ball.

That's a very simple example. The major component of what we call intelligence is purely predictive. Of course Bayesian inference also works the same way, etc.

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Jensson 3 days ago | parent | next [-]

> The major component of what we call intelligence is purely predictive

Then what is creativity? Creativity is not predictive and is the most important part of human intelligence, since it isn't about figuring out if a situation leads to good things, its about finding a new kind of situation that leads to good things.

Don't say "we do totally random things and try to predict those outcomes", there is nothing supporting that since we have tried that with computers and that doesn't result in creativity anything like humans, we don't know how human creativity works.

	▲	A_D_E_P_T 2 days ago \| parent [-]
		So we've got a temporal-spatial sense, a general predictive function, the capacity for abstraction, independent volition, and a sense of relational context. Creativity shows up when an agent uses that predictive machinery not only to forecast immediate sensory consequences, but to (a) simulate many alternative internal models or actions (counterfactuals), usually in a self-directed way with an end or goal in mind, (b) predict how those alternatives will be interpreted by other agents or by itself in the future, and (c) select from those alternatives according to an intrinsic/extrinsic valuation that rewards novelty, surprise, utility, or aesthetic pleasure. In other words it's a form of guided meta-prediction. From a very different perspective, the TRIZ guys have tried to figure out creativity, with results that are at least interesting. Ultimately, what they have to teach is that non-artistic creativity also takes certain characteristic forms.

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devmor 3 days ago | parent | prev [-]

> The major component of what we call intelligence is purely predictive.

Making more unfounded, nonsensical claims does not reinforce your first unfounded, nonsensical claim.

I'm sure statisticians would love it if the human mind were an inference machine, but that doesn't make it one. Your point of view on this is faith-based.

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cubefox 2 days ago | parent [-]

His view aligns both with a leading neuroscience explanation of the brain (predictive coding [1]) and with Active Inference / the Free Energy principle [2] from optimal control theory. A similar theory of intelligence, called H-JEPA (hierarchical joint embedding predictive architecture) [3] is also put forward by Yann LeCun, a major AI pioneer. Another AI pioneer, Jürgen Schmidhuber, subsequently criticized LeCun's theory, but not for being faulty, but for rehashing ideas published in several papers from the 1990s onward. [4]

1: https://en.wikipedia.org/wiki/Predictive_coding

2: https://en.wikipedia.org/wiki/Free_energy_principle#Active_i...

3: https://openreview.net/forum?id=BZ5a1r-kVsf

4: https://people.idsia.ch/~juergen/lecun-rehash-1990-2022.html

	▲	devmor a day ago \| parent [-]
		The Bayesian brain model is an unfalsifiable, faith-based mechanism - as I alluded to in my previous comment. Real science is done with it as a starting point, but it is not real science and claiming that it is an accurate representation of the human mind carries as much merit as claiming that "the soul" is what powers human intellect.