Yes, AI—especially LLMs—have definitely rekindled interest in semantic technologies, but more from a pragmatic angle than the original Semantic Web vision. Knowledge graphs, ontologies, and structured data are now seen as valuable tools for improving things like grounding, retrieval-augmented generation (RAG), and reasoning in agents. The difference is that instead of expecting the whole web to be semantically annotated (which didn’t scale well), now organizations are building domain-specific graphs to augment AI performance. It’s like the Semantic Web finally found its killer app—just not in the way it was initially imagined.
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Yes, AI—especially LLMs—have definitely rekindled interest in semantic technologies, but more from a pragmatic angle than the original Semantic Web vision. Knowledge graphs, ontologies, and structured data are now seen as valuable tools for improving things like grounding, retrieval-augmented generation (RAG), and reasoning in agents. The difference is that instead of expecting the whole web to be semantically annotated (which didn’t scale well), now organizations are building domain-specific graphs to augment AI performance. It’s like the Semantic Web finally found its killer app—just not in the way it was initially imagined.