AI

Since the launch of the Gemini 2.0 Flash model family, developers are discovering new use cases for this highly efficient family of models. Gemini 2.0 Flash offers stronger performance over 1.5 Flash and 1.5 Pro, plus simplified pricing that makes our 1 million token context window more affordable. Today, Gemini 2.0 Flash-Lite is now generally available in the Gemini API for production use in Google AI Studio and for enterprise customers on Vertex AI. 2.0

Retrieval-Augmented Generation (RAG) is a powerful technique that enhances language models by incorporating external information retrieval mechanisms. While standard RAG implementations improve response relevance, they often struggle in complex retrieval scenarios. This article explores the limitations of a vanilla RAG setup and introduces advanced techniques to enhance its accuracy and efficiency. The Challenge with Vanilla RAG To illustrate RAG’s limitations, consider a simple experiment where we attempt to retrieve relevant information from a set of