I made the direct comparison to neural nets as it uses a very similar method to them (i.e. using weights as parameters and minimizing a cost function via gradient descent) but is simpler (gets rid of layers, neurons, activation functions, etc).
I never stated "AGI means solving polynomials". Based on how far LLMs have come, function approximation seems to play a role in it.
Tail recursion is when the recursive call is last in a function; this algorithm uses breadth-first search to simultaneously 1. search the space of inputs and outputs 2. find the smallest set out of outputs to reach a reward. Again, tail recursion is completely irrelevant.
I overcame a weak sense of self by learning to draw boundaries. I can't stress how important this is. When you have weak boundaries, you let others control your life. Learn to draw clear boundaries that must never be crossed. I recommend googling the problem.