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How to Use Generative AI to Answer Questions on Top of Company's Knowledge Base
The number one kind of generative AI use case or requests is retrieval augmented generation. The way companies do that typically is that let's just take the use case of being able to answer questions on top of company's knowledge base. Now an embedding model is a type of large language model that takes a text as input and returns embeddings which capture the semantic meaning of the input text. And then under the hood, you basically do some matching between the embeddings for the user query and all theembeddings stored in your vector database.