AI Agents for Data Analysis with Shreya Shankar - #703
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Evaluate with Intent: How to Architect Data Processing
Evaluation in data processing is complex and context-dependent, requiring clear definitions that may evolve. Integrating a large language model (LLM) transforms evaluative thinking, emphasizing the need for adaptable architectures. Leveraging generation agents allows for the rewriting of high-level operator specifications into more refined sub-pipelines, enhancing operational efficiency. These rewrites can take various forms, such as breaking down tasks into manageable components or extracting specific fields from documents through multiple operations. This modular approach enables the generation of numerous candidate plans, optimizing the data processing workflow.
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