Enhancing GPT's Response Accuracy Through Embeddings-Based Search

This comprehensive guide explores the method of using GPT for question answering on topics beyond its training data, via a two-step Search-Ask approach. Initially, relevant textual content is identified using embedding-based search. Subsequently, these sections are presented to GPT, seeking answers to the posed queries. This process leverages embeddings to locate pertinent sections within text libraries that likely contain answers, despite not having direct phrasing matches with the inquiry. A notable advantage discussed is GPT's enhanced accuracy in providing answers due to the contextual clues supplied by the inserted texts, compared to fine-tuning methods that are less reliable for factual information.

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