AI inference can deliver faster, more accurate predictions to organizations of all sizes—but building a platform for production AI inference is hard. Real-world use cases require different types of AI model architectures, and the models can contain hundreds of millions of parameters. Models are trained in different frameworks and have different formats. Applications have different requirements, and then there are different execution environments.