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Embrace Flexibility in ML Development
Optimizing for flexibility in machine learning platforms is crucial for delivering AI capabilities across a company. Supporting a diverse range of models, hardware accelerators, and frameworks allows teams to stay agnostic and quickly adopt the latest technologies. The ability to integrate various tools, like Ray for inferencing, enhances scalability and adaptability, enabling engineers to efficiently implement and fine-tune solutions tailored to specific business needs.