An LLM is a lossy encyclopedia

I prefer to think of LLMs as lossy predictors. 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.

In the real world, with countless fuzzy factors, no predictor can ever be perfectly lossless. The only real difference, for me, is that LLMs are lossier predictors than human minds (for now). That's all there is to it.

Whatever analogy you use, it comes down to the realization that there's always some lossiness involved, whether you frame it as an encyclopedia or not.

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.)

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.

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.