In this comprehensive episode, we break down the inner workings of large language models and multimodal AI systems that power tools like ChatGPT and Gemini. You'll gain clear insights into the technical infrastructure that determines whether your content gets discovered, cited, and utilized by these increasingly influential AI systems.

Key Takeaway: Discover how vector databases store mathematical representations of your content, how embedding spaces organize information in conceptual neighborhoods, and how retrieval-augmented generation (RAG) finds and uses your content to answer user queries. Most importantly, learn practical strategies to optimize your content for these technical systems without getting lost in jargon.

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