So to make predictions about general intelligence is just crazy.
And yeah yeah I know that OpenAI defines it as the ability to do all economically relevant tasks, but that's an awful definition. Whoever came up with that one has had their imagination damaged by greed.
https://en.wikipedia.org/wiki/Ontology
Or: just try, then try your best to find ways your definition fails. You should find it challenging, to put it mildly, to create a bulletproof definition, if you’re really looking for angles to attack each definition you can think of. They’ll end up being too broad, or too narrow. Or coming up short on defining when exactly a non-chair becomes a chair, and vice-versa, or what the boundaries of a chair are (where chairness begins and ends).
And if that one is tricky…
So I'm asking how you define a definition as "too broad".
Because my perspective is that definitions that are in fact too broad are unimportant because no one uses them.
Universal definitions? Extremely hard.
Even when we "generalize" our intelligence, we can only extend it within the realm of human senses & concepts, so it's still intelligence specific to human concerns.
- despite our difference we have the same kind of intelligence
- our intelligences intersect, but there are capacities that each has that the other doesn't
?
It seems like for either to be true there would have to be some place of common ground into which we could both generalize independently of our circumstance. Mathematics is often thought to be such a place for instance, there's plenty of sci fi about beaming prime numbers into space as an attempt to leverage that common ground. Are you saying there aren't such places? That SETI is hopeless?
It's just not guaranteed.
> Even when we "generalize" our intelligence, we can only extend it within the realm of human senses & concepts, so it's still intelligence specific to human concerns.
...then we might fail to recognized them as intelligent when we meet them. Same goes for emergent artificial doohickeys. A theory that allows for generalization might never fine an example of it, but it's still better than a theory which doesn't because the second sort surely won't.
Unfalsifiable statements are worthless because they can't be tested.
So, at the very least, there's no point in humans trying to theorize about intelligence so general that it expands beyond human comprehension.
Basically, in the context of universal intelligence, I'm an atheist & you're agnostic.
I think you can get pretty far starting from behavior and constraints. The brain needs to act in such a way as to pay for its costs. And not just day to day costs, also ability to receive and give that initial inheritance.
From cost of execution we can derive an imperative for efficiency. Learning is how we avoid making the same mistakes and adapt. Abstractions are how we efficiently carry around past experience to be applied in new situations. Imagination and planning are how we avoid the high cost of catastrophic mistakes.
Consciousness itself falls from the serial action bottleneck. We can't walk left and right at the same time, or drink coffee before brewing it. Behavior has a natural sequential structure, and this forces the distributed activity in the brain to centralized on a serial output sequence.
My mental model is that of a structure-flow recursion. Flow carves structure, and structure channels flow. Experiences train brains and brain generated actions generate experiences. Cutting this loop and analyzing parts of it in isolation does not make sense, like trying to analyze the matter and motion in a hurricane separately.
Simulating that is a long way away - so the only possibility is that brains have some sort of redundancy and we can optimise that away. Though computers are faster than brains so its possible maybe, how much faster? So lets say a neuron does its work in a mS and we can simulate this work in 1uS, ie a thousand times faster - thats still a lot. Can we get to a million times faster? even then its still a lot. Not to mention the power required for this.
Even if we can fit a million neurons in a CPU thats still 90 million CPU's. Only 10% are active say, still 9 million CPU's, a thousand times faster - 9,000 cpu's nearly there but still a while away.
The LLM stuff seems most distinctly to not be an emulation of the human brain in any sense, even if it displays human-like characteristics at times.
Ultimately this comes down to the philosophy of language and of the history of specific concepts like intelligence or consciousness - neither of which exist in the world as a specific quality, but are more just linguistic shorthands for a bundle of various abilities and qualities.
Hence the entire idea of generalized intelligence is a bit nonsensical, other than as another bundle of various abilities and qualities. What those are specifically doesn’t seem to be ever clarified before the term AGI is used.