But under the hood so many of the frameworks do this anyways.

Not really. The whole idea of self-modifying code is changing preprogrammed algorithm to something new. The whole idea of any JIT compilation is to preserve preprogrammed algorithm intact. You don't get program you never wrote using JIT compilation based language (well, sometimes you do, but this accounted as bug, not as intended behaviour). Also you will never get a code that executes differently on subsequent calls because it was changed in between. Same piece of code will always give same result with same input data. That's not the case with self-modifying code.

To illustrate what I mean, imagine funtion, say func(a,b){return a+b;}. Self-modifying approach could make same function be func(a,b){return a+b+2;} at one monent and func(a,b){return 3*a+b;} at another moment. Add to that conditions, cycles calling other functions and all that stuff.

Apart from self-modifying code some other things is necessary for real AI - undefined behaviour, accidental "mutations", computed goto's and all that stuff.

Why all that things is importnant for AI? Because intelligence is unpredictable. You can't just calculate the outcome of intelligent entity decision. And you can't speak about intelligence when you could predict a result with 100% certainity which is a core and absolute must for modern computing paradigm. Computer science was dragged by all that "good practice"/"bad practice" narratives as far from any possible AI as possible.

Our perception of intelligence and life in whole is connected with unpredictability of both. Take a look at following analogy - you could easily found ones who account their car as alive among owners of old cars. But you will not find any among owners of new cars. The difference in unpredictability. New car works as expected, everything runs as designed and it behave same in same situations. Old car is weared, there are more randomness in its behaviour due to backlashes, working regimes shifted, something creak occasionally and so on. It could give different results in same circumstances. Of course that's all have exact reasons, sometimes very complex, but for the owner, who don't want to dig deep it's just alive. And if you fix everything, return predictability, this mistery of life in piece of metal will disappear.

Same with intelligence. We will never account something predictable as intelligent. We here make fun over sheeple, as human NPC's accounting them unintelligent. Why? because they are predictable, like some machines or preprogrammed algorithms. And so we will never accept any AI if it will be predictable. And with modern programming approaches nothing unpredictable could be created.

But under the hood so many of the frameworks do this anyways.

Not really. The whole idea of self-modifying code is changing preprogrammed algorithm to something new. The whole idea of any JIT compilation is to preserve preprogrammed algorithm intact. You don't get program you never wrote using JIT compilation based language (well, sometimes you do, but this accounted as bug, not as intended behaviour). Also you will never get a code that execute differently on subsequent calls because it was changed in between. Same piece of code will always give same result with same input data. That's not the case with self-modifying code.

To illustrate what I mean, imagine funtion, say func(a,b){return a+b;}. Self-modifying approach could make same function be func(a,b){return a+b+2;} at one monent and func(a,b){return 3*a+b;} at another moment. Add to that conditions, cycles calling other functions and all that stuff.

Apart from self-modifying code some other things is necessary for real AI - undefined behaviour, accidental "mutations", computed goto's and all that stuff.

Why all that things is importnant for AI? Because intelligence is unpredictable. You can't just calculate the outcome of intelligent entity decision. And you can't speak about intelligence when you could predict a result with 100% certainity which is a core and absolute must for modern computing paradigm. Computer science was dragged by all that "good practice"/"bad practice" narratives as far from any possible AI as possible.

Our perception of intelligence and life in whole is connected with unpredictability of both. Take a look at following analogy - you could easily found ones who account their car as alive among owners of old cars. But you will not find any among owners of new cars. The difference in unpredictability. New car works as expected, everything runs as designed and it behave same in same situations. Old car is weared, there are more randomness in its behaviour due to backlashes, working regimes shifted, something creak occasionally and so on. It could give different results in same circumstances. Of course that's all have exact reasons, sometimes very complex, but for the owner, who don't want to dig deep it's just alive. And if you fix everything, return predictability, this mistery of life in piece of metal will disappear.

Same with intelligence. We will never account something predictable as intelligent. We here make fun over sheeple, as human NPC's accounting them unintelligent. Why? because they are predictable, like some machines or preprogrammed algorithms. And so we will never accept any AI if it will be predictable. And with modern programming approaches nothing unpredictable could be created.