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The MLP from Tutorial 01 is stateless. Feed it 'c' and it predicts /k/. Feed it 'c' again after reading "ch" and it still predicts /k/. It has no memory of what came before. That's a real problem. In ...

The Transformer has more moving parts than the MLP or LSTM. You're not just wiring layers together — you're wiring them together with attention, and attention has several subtle details that make it ...