Early graphics accelerators evolved from simple fixed-function pipelines into the programmable CUDA architecture. This shift enabled general-purpose computing on GPUs, fueling the current deep learning boom. Developers now rely on these parallel processing capabilities for massive tensor operations. Understanding this lineage clarifies why Nvidia dominates the current AI hardware market.