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pre-trained language model (e.g., GPT, BERT, T5 or from Groq) that creates responses by incorporating the retrieved information.
id="app-details-left"> https://bolt.new/~/sb1-gxtwwzjb Inspiration: RAG combines retrieval systems with Generative AI models to produce accurate and relevant responses. It is particularly useful for applications that require up-to-date, fact-based, or domain-specific responses. when an AI model generates incorrect or misleading results. This can happen in any type of AI model, including natural language processing (NLP) models and computer vision models. The model's inability to provide updated information because it was trained on a fixed dataset that does not include newer data. What it…
Description excerpted from the original listing, which is linked below.
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