@Meari_V2_0_G: This is the driving force behind my project. But in reality, what AI needs to find can't be retrieved if the keyword is guessed wrong. Just like today I said I wrote a handwritten AC automaton but the AI didn't find it — because its module name isn't that. However, vectors are not useless. You can never search for something like 'What's the weather like today?' using keyword search. Three...

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The author discusses the pros and cons of keyword search and vector search in AI, suggesting that multiple search strategies should be combined and registered with the Agent, and cites a view that free traditional tools might destroy the entire vector database industry.

This is the driving force behind my project. But in reality, what AI needs to find can't be retrieved if the keyword is guessed wrong. Just like today I said I wrote a handwritten AC automaton but the AI didn't find it — because its module name isn't that. However, vectors are not useless. You can never search for something like 'What's the weather like today?' using keyword search. It makes sense to register three search strategies with the agent at the same time.
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That is the original motivation behind my project. However, in practice, if the AI can’t guess the right keyword for what it’s looking for, it won’t find it. For example, today I said I wrote an AC automaton by hand, but the AI didn’t find it—because the module name isn’t called that. But vectors are not entirely useless. You can never use keyword search to search for something like “How’s the weather today?” It makes sense to register three search strategies simultaneously for the agent.

How To Prompt (@HowToPrompt__): The entire vector database industry just got destroyed by A free tool from 1974.

For the last two years, every company building AI has obsessed over “RAG” (Retrieval-Augmented Generation).

They spent millions on complex vector databases, semantic search, and embedding models.

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