Don't Start With RAG: Lessons From Building an Automotive AI Pipeline
Our take: Practical insight on data-first AI pipelines; useful but case-study based, not research.
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An automotive AI pipeline prioritizes understanding input reliability and normalizing diverse data sources before applying LLMs, rather than starting with trendy tools like RAG and vector databases.
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