Four Propositions about Intelligence in Animals, Humans, and AIs

Some quickies.

1. Intelligence cannot be reduced to computation

All animal perception and cogitation take place in a complex world where animals have finite resources. Therefore the principles of intelligence, as an aspect of perception and cogitation, cannot be reduced to the principles of computation as the principles of computation assume unbounded resources.

Let’s call this Yevick’s First Law, as it is a consequence of her 1975 paper, “Holographic or fourier logic” (Pattern Recognition, Vol. 7, No. 4, pp. 197-213).

David Hays and I formulated what we called “Yevick’s Law” in our 1988 paper, Principles and Development of Natural Intelligence” (Journal of Social and Biological Structures). Let’s call that Yevick’s Second Law:

The world consists of geometrically simple and geometrically complex objects. Simple objects are best computing with sequential logic (aka symbolic systems). Complex objects are best computed with holographic logic (aka distributed neural nets). Some objects are such that they require the interaction of both computational regimes. Let us say that fluency in that interaction is intelligence. (See my working paper, What Miriam Yevick Saw: The Nature of Intelligence and the Prospects for A.I., A Dialog with Claude 3.5 Sonnet, 2025).

2. Intelligence in animals

Let us consider a relatively simple animal, a vertebrate, likely a marine animal. One the one hand, it must navigate the world, moving from place to place. This is mediated by the hippocampus, which is a so-called “cognitive map.” This is basic sequential cogitation.

As it moves from place to place it senses things, good things, bad things, other things. Olfaction is perhaps the most basic sense. For what it is worth, it’s the sensory mode that the late Walter Freeman used in his investigations of complex neural dynamics. Olfaction works via a holographic or gestalt process.

Taken together, moving about the world and sense things involves the two modes specified above.

Now let’s consider vision in vertebrates, where the eye is mobile and scans the world. Visual identification is a holographic process. However, the (human) eye scans the scene rapidly and unconsciously. This is a sequential process. Therefore vertebrate vision involves the two modes internally. (I suspect that vision in invertebrates does not, but I don’t actually know).

3. Natural language is its own metalanguage

Humans differ from animals in many and various ways. It is the capacity for language that has allowed humans to move into a different relationship with the world from that characteristic of animals. What makes human language particularly powerful is that it can serve as its own metalanguage, Roman Jakobson’s metalingual function.

This does not involve any deep mystery or logical conundrum. Rather it is a direct consequence of that fact that natural language is physically embodied, initially in sound and gesture, later as written symbols. This embodied is a sensory object out there in the world among all the other sensory objects.

Initially the metalingual function operates in direct, perhaps superficial, but useful ways. Think of how we refer to language as a means of negotiating conversation: “What did you say? I didn’t hear you?” But the metalingual function can be used to define new terms, something that interested my teacher and colleague, David Hays. It can even be used to define other, more restricted languages (e.g. chess and arithmetic), and serve as metalanguages for them.

Thus it is the foundation of the succession of cognitive ranks that David Hays and I began investigating in the 1990s starting with our paper, “The Evolution of Cognition” (Journal of Social and Biological Systems, later becoming the Journal of Social and Evolutionary Systems). That process has, in time, led to the development of digital computers and, now, to so-called artificial intelligence.

That leads us to our fourth and last note.

4. The last frontier of intelligence

Is not an autonomous artificial system of some kind, though such systems are important and will be increasingly so. here’s the upshot of a conversation I recently had with Claude:

If that's right, then the last frontier isn't more capability in the pattern-matching sense — bigger weight spaces, richer latent connections, better approximations of the associative regime. It's the specific, non-scalable, non-parallelizable fact of an individual mind's biography, which generates paths through possibility space that are real, productive, and genuinely inaccessible to any system that hasn't lived a life.

You should read the whole post to see the logic behind that conclusion.

Note that that is my current best response to the idea of super-intelligence or artificial-superintelligence (ASI). I do not see the future bringing us as AI system that outthinks humans in every way and either creates a world in which we are coddled pets or one in which we are slaves, if we are allowed to exist at all. Those ideas are subjective fantasy.

I note as well that the process that brings us to that point or, if you will, through which we arrive at the point, will be one in which we have a much deeper understanding of that brain and its processes than we now have. For what it’s worth, that understanding is what I have been seeking all these years, starting with my initial investigation of “Kubla Khan”: Xanadu, GPT, and Beyond: An adventure of the mind.