Today's leading generative AI applications have workloads that span high performance GPU compute, CPU preprocessing, data-loading, and orchestration — often spread across a combination of Python, C++/Rust, and CUDA C++ — which increases the complexity and slows down the cycle of innovation. This talk explores the capabilities and power of the Modular Mojo programming language and Modular Accelerated Xecution (MAX) platform, which unifies CPU and GPU programming into a single Pythonic programming model that is simple and extensible. This results in reduced complexity and improved developer productivity, and streamlines innovation. We'll walk through CPU and GPU support with real-world examples, providing details of how AI application developers can use MAX and Mojo to define an end-to-end AI pipeline and overcome the complexities.