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For about fifteen years, almost nobody asked it.
Funding dried up. The field moved on. Neural networks became a backwater, something serious researchers didn't touch.
But a small group kept going. They had little funding and little recognition. They worked on one question: if a network makes a mistake at the output, can you trace that mistake backwards, layer by layer, until you find the weights that caused it? Can you assign blame?
They found a way.
With it, everything the Perceptron couldn't do became possible. The limit was never the idea. It was just that nobody had solved the training problem yet.
They were right.