[HuShifang]

Not an endorsement, but here's an argument that AGI is computationally intractable (edit: at least via ML). https://irisvanrooijcogsci.com/2023/09/17/debunking-agi-inev...

[ceejayoz]

"AI is impossible" is a tough argument, given the existence of non-A I.

"Machine learning isn't the route to AI" is something you could more reasonably argue, but that's a drastically narrower claim.

[jameshart]

Intractable and impossible are very different claims.

NP Hardness is a statement about the asymptotic difficulty of solving a problem at ever larger scales. It says ‘if you have a way to solve this problem at size n, that way will scale worse than polynomially when you try to apply it to a problem at size 2n’.

Which might place limits on the practicable scale of how big an n your approach gets to work for. But if your approach works practically for a big enough n to make AGI then your approach works - NP Hardness doesn’t matter.

And since we know that finite mass lumps of finite numbers of gray cells are capable of GI, we have a reasonable expectation that there is some n for which AGI might be possible.