The article delves into GenAIOps, which stands for Generative AI Operations, offering practices and methodologies to develop and operationalize Generative AI solutions within enterprises. It addresses challenges faced by enterprises adopting Generative AI and explores key components, best practices, challenges, and future trends of GenAIOps in the AI landscape.
GenAIOps encompasses MLOps, DevOps, DataOps, and ModelOps for all generative AI workloads, including language, image, and multimodal tasks. It introduces new capabilities like synthetic data management, embedding management, agent/chain management, guardrails, and prompt management to enhance generative AI operations.
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