• transformer — The neural network architecture behind modern AI models, built on attention — letting every word directly consider every other word in parallel.
• inference — Running a trained model to get answers — the phase where AI is actually used, as opposed to trained.

It explains, at the hardware level, why dedicated NPU silicon designed for CNNs struggles with transformer inference, and what that implies for where AI acceleration is heading on Apple silicon.

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