@MaximeRivest: Compound AI System for Images are way under appreciated. We need gepa, dspy, autoresearch style optimization to go from…

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Summary

Maxime Rivest argues that compound AI systems for images are undervalued and suggests leveraging optimization frameworks like DSPy and GEPA to automate pipeline creation involving SAM and classifiers.

Compound AI System for Images are way under appreciated. We need gepa, dspy, autoresearch style optimization to go from: image -> area where the prompt to SAM, the finetuned classifier, the scipy image transformations and numpy custom pipelines are all automatically optimized by a big reflection model.
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@MaximeRivest: https://x.com/MaximeRivest/status/2055293570119065875

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MaximeRivest explains DSPy's five core components—Optimizers, Signatures, LMs, Modules, and Adapters—and argues that effective AI engineering requires mastering these elements, highlighting the often-overlooked role of rendering structured outputs.