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So Minsky and Papert were right about that part.
The Perceptron can only handle problems where inputs each point toward the answer independently. The moment a problem requires understanding relationships, one input changing the meaning of another, it fails. Every time. With no way out.
That's not something you can fix by training longer or giving it more data. It comes from what multiply-and-add is at its core, and that's not going to change.
One neuron, one ceiling. That was the wall, and no amount of training could move it.