> The architecture is feedforward, which implies it answers each query in an amount of time bounded by some function. Are you talking about each step where it

> The architecture is feedforward, which implies it answers each query in an amount of time bounded by some function. Are you talking about each step where it produces a new output token? If so, sure. But how is that different from any CPU that executes an instruction? If you mean in general, doesn't it have a feedback loop where its own previous outputs affect future outputs? You could ask it to emulate this Basic program: 10 PRINT "Hello" 20 GOTO 10 And it would in principle output "Hello" forever (but in practice segfault after 32k tokens), right? (I just tried something like this in ChatGPT. It did emulate a few iterations which it output, but then it performed a halting analysis and told me "As there is no condition to exit the loop, the program will continue to run in an infinite loop until it is manually interrupted." - not sure who's point that proves :-) > By the time-hierarchy theorem there exist computable functions with arbitrarily high asymptotic complexity. You're clearly more versed in the theory than I am with just an average CS level understanding. But isn't that the same as "with the caveat that it can only execute 32k instructions before it has to stop"? I'm not sure what the limits of the current GPTs are. It's far from clear that they'll evolve into AGI, we might still see a new AI winter in the future. But at the same time it looks like we've stepped up to a completely new level of capabilities.