Hands on If you've been following the enterprise adoption of AI, you've no doubt heard the term "RAG" thrown around.
Build a large language model AI Chatbot using Retrieval Augmented Generation
The technique, which stands for extended generation for recycling, has been touted by everyone from Nvidia's Jensen Huang to Intel chief savior Pat Gelsinger as what will make AI models useful enough to justify investments in relatively expensive GPUs and accelerators.
The idea behind RAG is simple: Instead of relying on a model pre-trained on a limited amount of public information, you can take advantage of an LLM's ability to analyze human language to interpret and transform information contained in an external database .
Critically, this database can be updated independently of the model, allowing you to improve or refresh your LLM-based app without having to retrain or fine-tune the model every time new information is added or old data is removed.
