Artificial intelligence, particularly deep learning, operates on principles fundamentally different from traditional computing tasks. Unlike sequential processing where a CPU tackles one instruction after another, AI algorithms thrive on massive parallelization. Think of it as solving a puzzle: a traditional CPU might place pieces one by one, while AI hardware allows thousands of “workers” to place pieces simultaneously. This core distinction arises from the mathematical operations inherent in neural networks –
