MAX 24.3 has been launched, featuring the new MAX Engine Extensibility API that enables developers to create unified AI pipelines using a next-generation compiler and runtime library for optimized AI inference performance. Supporting frameworks such as PyTorch, ONNX, and native Mojo models, the MAX Engine offers low-latency, high-throughput execution on diverse hardware, while the MAX Graph APIs allow for the development of custom inference models. Key updates in this release include Custom Operator Extensibility using the Mojo programming language, which simplifies the integration of bespoke operations into AI pipelines, improvements in the Mojo language and standard library, and a reduction in package size by removing TensorFlow from the standard MAX package. The release also emphasizes community-driven innovation, highlighting significant contributions to the Mojo standard library and facilitating easier development of custom operations. MAX 24.3 introduces a more efficient development cycle with built-in performance optimizations, portability, and a unified approach to AI workflows, positioning it as a versatile tool for AI development across various platforms.