3 ms·
I don't see how that would follow. If we are talking about "intelligence" in the formal sense of induction/prediction then it is a profoundly memory-hard proble
by jandrewrogers 7mo ago
I don't see how that would follow. If we are talking about "intelligence" in the formal sense of induction/prediction then it is a profoundly memory-hard problem as a matter of theory. This is to "learning" what the speed of light is to physics.
You can't replace the larger simulation required (i.e. more state/RAM) with a faster processor.
- neonstatic 7mo agoSticking with the computation analogy, it could be a long-term memory look up. If memories were passed down the generations, people could simply memorize actions of individuals deemed smarter. Over a large sample size, a heuristic would emerge. Kind of like knowing there is always a sunset following a sunrise without understanding the solar system.
- jandrewrogers 7mo agoIt is a zero sum game because you have a finite state budget for representing heuristics. Increasing the "smartness" (and therefore state required) of one heuristic necessarily requires reducing the smartness of other heuristics. The state is never not fully allocated, the best you can do is reallocate it. This places an upper bound on the complexity of the patterns you can learn. At the limit you could spend 100% of resources building a maximally accurate model of a single thing but there are limits to ROI. Pre-digested learning makes it more efficient to acquire heuristics but it doesn't change the cost of representing it. Some simple state machines are resistant to induction by design e.g. encryption algorithms.
- Detrytus 7mo agoI think that's kind of how all the religions were started. Smart people being tired of reasoning with dumb ones and instead going with "do this, because that's the will of God".