This is exactly the gap that Retrieval-Augmented Generation (RAG) with vector embeddings was built to fill — by matching meaning, not just keywords. In this article, we’ll break down how each approach works, where each one wins, and why production systems increasingly use both together.
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昨日,理想汽车官方宣布,旗下马赫100芯片的研究论文《M100: An Orchestrated Dataflow Architecture Powering General AI Computing》近日获ISCA 2026(国际计算机体系结构年会)录用,理想汽车也因此成为汽车行业首家在该会议工业分区(Industry Track)获得论文录取的企业。