A Q&A From Inference To Training: The Inside Story Of Baseten’s Newest Product

Baseten has introduced a new training infrastructure designed for flexibility and scalability, allowing teams to run their existing code on scalable compute without complex abstractions. This infrastructure is aimed at providing a seamless transition from training to deployment by integrating with Baseten's inference stack, making it suitable for custom models, audio models, and multi-node jobs. Early adopters like OpenEvidence and Oxen have utilized the platform to enhance inference speeds and build comprehensive platforms. Unlike point-and-click solutions, Baseten's platform supports diverse model training needs, offering users the ability to experiment and optimize their models with hands-on control over the code and parameters. The infrastructure is designed for easy migration from existing setups, offering on-demand compute and persistent storage to streamline the iteration process. Baseten's focus on inference expertise enhances its training offering, ensuring that models transition smoothly into deployment. The development process involved close collaboration with early customers to refine the product, leading to features like private Docker registry support based on feedback. Baseten’s training infrastructure allows for direct interaction through APIs as well as CLI, making it adaptable for various use cases and platforms.