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GPU Considerations, Labeling Privacy, Rapid Fine Tuning, and the Role of Private Eval Pipelines to Benchmark New Models

MLOps.community

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Intro

This chapter explores the complexities of training AI models for agentic systems, addressing issues like model depreciation and ineffective benchmarks. It also examines optimization strategies for scaling AI solutions to handle high user interactions effectively and affordably.

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