Profiling in PyTorch (Part 2): From nn.Linear to a Fused MLP

# Plain-English Summary AI researchers have found ways to make the mathematical operations inside AI models run faster by combining multiple steps into one, kind of like how a dishwasher is more efficient than washing dishes one at a time. This article walks through the technical process of speeding up these operations, which ultimately means AI models can run quicker and use less computing power—something that matters for anyone running or paying for AI services.