Large language models represent text using tokens, each of which is a few characters. Short words are represented by a single token (like "the" or "it"), whereas larger words may be represented by ...

Other document elements like tables, diagrams and graphs often become an incoherent jumble of symbols and text which is unusable by the LLM. The downstream effect is that RAG systems perform well ...

Enter retrieval-augmented generation (RAG), a framework that’s here to keep AI’s feet on the ground and its head out of the ...

Finally, The LLM provides a polished, personalized answer, with real-time data. An AI face in profile against a digital background. RAG isn’t just for tech geeks - it’s revolutionizing ...

Finally, The LLM provides a polished, personalized answer, with real-time data. RAG isn’t just for tech geeks - it’s revolutionizing customer support too. By pulling in detailed product info ...

RAG involves leveraging an external knowledge base to enhance the outputs of an LLM. By retrieving relevant information based on the input prompt, RAG can generate more accurate and informative ...