Understand retrieval-based AI models, how they differ from generative models, and why they power modern chatbots with accurate, fact-based responses.
More about Retrieval-based Models
Retrieval-based Models are AI systems designed to fetch and present the most relevant information from a predefined dataset or knowledge base. These models often utilize sparse retrieval methods for term-based matching or dense retrieval to capture semantic relationships.
Retrieval-based models are widely used in semantic search, question answering, and recommendation systems, where accuracy and relevance are crucial.