Are Intelligence and Generality Orthogonal?

Regarding the counterexample: I think it is fair to say that perfect orthogonality is not plausible, especially not if we allow cases with one axis being zero, whatever that might mean. But intelligence and generality could be still largely orthogonal. What do you think of the case of insects, as an example of low intelligence and high generality?

(I think not even the original orthogonality thesis holds perfectly. An example is the oft-cited fact that animals don't optimize for the goal of inclusive genetic fitness because they are not intelligent enough to grasp such a goal. So they instead optimize for similar things, like sex.)

↑ comment by Alexander (alexander-1) · 2022-07-19T10:26:08.237Z · LW(p) · GW(p)

Have you come across the work of Yann LeCun on world models? LeCun is very interested in generality. He calls generality the "dark matter of intelligence". He thinks that to achieve a high degree of generality, the agent needs to construct world models.

Insects have highly simplified world models, and that could be part of the explanation for the high degree of generality exhibited by insects. For example, the fact the male Jewel Beetle fell in love with beer bottles mistaking them for females is strong evidence that beetles have highly simplified world models.

I think it would perform worse than random.

How?

I think what people mean by intelligence is how well someone or something does on tests, stuff you measure with precision and recall. Then you do some arithmetic and you get a number, whether it's how many pieces of music you wrote or how many answers you got correct. Anything about intelligence outside of this context is actually a misnomer. They are rather talking about the process where the measure of intelligence can be deduced. A lot of it is dependent on the measurement of speed. That's why they usually give you time limit for shit like this.

Sorry - forgot about your comment.

1. Tasks that animals usually face? (Find food, a safe place to sleep, survive, reproduce ...)

2. This is an intriguing question. My first intuition: Probably not, because ...

   1. It seems evolution would have figured it out by now. After all, evolution optimizes heavily for generality. Any easily fixable blind spot would be a low hanging fruit for natural selection (e.g. by being exploited in inter-species competition).
   2. The level of generality of most animals seems very similar, and seems to have stayed similar for a very long time. Even the case of humans with apparently unusually high generality is, if the point in my post was right, not actually a case of unusually high generality, just a case of unusually high intelligence.
   3. More specifically: Generality seems to be strongly related to having a "real-world domain" (see Arbital link in the post), which even quite simple animals already satisfy. It is not clear what could be more general than that.

   On the other hand, perhaps there is indeed a higher level of generality, just not one which is a low-hanging fruit. Or one which is at least not a low-hanging fruit for the neuron-based brain structure which evolution on Earth is using in animals. (For example, brains are highly parallel but very slow in serial tasks, while silicon processors have a much higher serial speed. From computational complexity theory it is known that not all algorithms can be parallelized efficiently.)

   Another possibility is that some higher level of generality simply needs a certain amount of intelligence in order to "work". Which would mean that at some point in increasing intelligence, a phase-transition to a higher generality level would occur. The reason this has not happened yet in the history of evolution would simply be that a sufficient level of intelligence was not yet achieved.

   Thinking of it, one possible example for the latter having already happened once could be: cultural evolution. Only humans can (due to language, but also due to high intelligence) accumulate information across generations, learn, and adapt via culture instead of just via genes. That would indeed contradict my theory that humans are not significantly more general than other animals. If we accept the emergence of cultural evolution in humans as a phase transition to a higher level of generality, then there could be still other levels, inaccessible to us, but possibly accessible to a highly intelligent AI.

   Edit: Actually there were at least two phase transitions in "learning methods" of the above kind: Once via the emergence of cultural evolution some hundred thousand years ago, and once via the emergence of brains some hundred million years ago. If evolution is already some kind of learning process, then organisms with brains add one layer, and our "cultural" layer is a further one on top.

But classical chess computers like DeepBlue rely a lot on raw compute, yet this brute force approach is fairly useless in cases with large search space, like Go. I think the number of parameters in a neural network would be a better approximation.

Then we can even make the scaling hypothesis more precise: Presumably it says scaling is enough for (more) intelligence_1, but not for generality.