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One way to describe intelligence is as "the ability to understand something from a partial description". How minimalist this description can be is a measure of intelligence.
If your AI needs an excruciatingly exhaustive description of its task (as an explicit handcrafted program, or as a dense sampling of a static data manifold), it isn't actually intelligent. When you operate it, you're just querying the information you put into it. No autonomy.
Intelligence is the ratio with which your AI converts information about a task into skill at that task. Importantly, the task is typically not static, so "skill" here targets *future* situations, which may be very unlike past ones.
The conversion is from past operating space to future operating space.
It feels like this idea could be an optimality criterion. If an agent can behave ‘competently’ given just the minimum description length of the task itself. I’d think this is the minimum information required to do well at a task.
I think the most core description of intelligence is the ability to create and access links between simultaneous experiences. I'm not sure we can have any example of intelligence that doesnt use that principle and its darn neurally plausible too.
Thinking might mean, being able to understand and process concepts through analogies.https://twitter.com/FNeubueser/status/1211562678390538240?s=19 …
Kolmogorov Complexity?
sounds like implied context plays a role in that description, i wonder how much that overlaps with culture
Good. But we cannot be led by effects correlations (limited to perceptive tasks and never to bio-like cognition) as the intelligence effect subjective (by def) measurement. We have to urgently focus on the specification of the problem to be solved as a mechanism, not effect.
Then you’d want to focus upon consciousness, not intelligence; which is nearly as subjective as qualia itself.
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