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> Reinforcement learning is Turing complete [1], so if AI is possible at all, then it can be realised through RL. This seems like overstating your point. Nobod

> Reinforcement learning is Turing complete [1], so if AI is possible at all, then it can be realised through RL. This seems like overstating your point. Nobody has been able to rigorously define "AI" yet, so there's no way of saying whether it's possible with a Turing machine architecture. The human brain, at least, doesn't seem that similar to a Turing architecture. Neurons don't carry out anything like discrete operations. Maybe it's possible to run AGI on a Turing machine, maybe it's not, but there are more options than simply "possible with a Turing machine" or "completely impossible".

GregarianChild 6y ago
While I agree that we don't have an agreed upon definition of AI, the problem is firmly in the "I" part of AI! The "A" part is taken to mean implementable by a computer, i.e. a Turing machine. This is the content of the Church–Turing thesis [1]. [1] https://en.wikipedia.org/wiki/Church%E2%80%93Turing_thesis https://en.wikipedia.org/wiki/Church%E2%80%93Turing_thesis
- ForHackernews 6y ago
  > It states that a function on the natural numbers can be calculated by an effective method if and only if it is computable by a Turing machine. The article at the top of this thread is specifically about properties ("The Generalized Archimedean Property") that real numbers do not possess. There's also a little bit of slipperiness around the use of "AI" vs. "AGI" - you could easily argue (and people do!) that we've already achieved "AI" for many specialized domains. It's the General bit that seems to be the sticking point, and that this article focuses on.
joe_the_user 6y ago
Maybe it's possible to run AGI on a Turing machine, maybe it's not, Arguing from ignorance, of course nothing is knowable for certain. However there has been a lot of work on the universality of Turing machines, showing that a Turing machine can simulate any conceivable concept of finite computation and can approximate any conventional physical system. I think a more useful way to express your intuition is to note that if human-built AGI comes into existence, it might be runnable on a Turing machine but quite possibly not efficiently so.

GregarianChild 6y ago

While I agree that we don't have an agreed upon definition of AI, the problem is firmly in the "I" part of AI! The "A" part is taken to mean implementable by a computer, i.e. a Turing machine. This is the content of the Church–Turing thesis [1]. [1] https://en.wikipedia.org/wiki/Church%E2%80%93Turing_thesis https://en.wikipedia.org/wiki/Church%E2%80%93Turing_thesis

ForHackernews 6y ago
> It states that a function on the natural numbers can be calculated by an effective method if and only if it is computable by a Turing machine. The article at the top of this thread is specifically about properties ("The Generalized Archimedean Property") that real numbers do not possess. There's also a little bit of slipperiness around the use of "AI" vs. "AGI" - you could easily argue (and people do!) that we've already achieved "AI" for many specialized domains. It's the General bit that seems to be the sticking point, and that this article focuses on.

joe_the_user 6y ago

Maybe it's possible to run AGI on a Turing machine, maybe it's not, Arguing from ignorance, of course nothing is knowable for certain. However there has been a lot of work on the universality of Turing machines, showing that a Turing machine can simulate any conceivable concept of finite computation and can approximate any conventional physical system. I think a more useful way to express your intuition is to note that if human-built AGI comes into existence, it might be runnable on a Turing machine but quite possibly not efficiently so.