ML Workflows with Temporal: Optimizing AI and data engineering
Apr 22, 2024
Summary
This post details how Temporal can be used to orchestrate model training, testing, and deployment, and manage complex data pipelines. It highlights the use of Workflows and Activities for reliable execution, automatic retries, and state management. The post also discusses optimizing GPU costs by running intensive workloads only when needed through Task Queues, and orchestrating multiple AI pipelines together.
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