Summary
Foundation models are applied to structured data tasks within the modern data stack to automate data workflows such as SQL generation, data cleaning, and entity resolution. Production deployment challenges like processing scale, prompt brittleness, and a lack of domain-specific knowledge are addressed using techniques like model distillation, prompt ensembling, and retrieval-augmented generation.
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