Anthropic has recently introduced ‘Contextual Retrieval’ for Claude, a method that they believe dramatically improves the retrieval step in Retrieval-Augmented Generation (RAG). Following the launch of Claude for Enterprise and prompt caching, which helps the LLM models cache, people are already excited about its potential for coding tasks. This new feature enhances how AI helps […]
Category: RAG
Google has recently announced DataGemma, a pair of instruction-tuned models engineered for better accuracy. It’s interesting for two main reasons: 1. It’s trained on vast real-world data to mitigate the challenge of hallucinations. 2. It’s open-source. And with the recent announcement of OpenAI o1—also designed with accuracy and reasoning in mind—people have started to draw […]
In this blog post, we will explore the top 10 vector databases used for building LLM applications. Here’s a primer on how to build your own LLM applications. Now, let’s jump directly into it. Which is the best Vector Database? Comparing the top 10 candidates. 1. Pinecone Pinecone is a state-of-the-art vector database that is […]
Vector databases have recently gained popularity since the launch of ChatGPT. Previously, they were used in applications for similarity search, recommendation systems and image recognition. However, they now have become a critical tool for building LLM and RAG applications. There are several different types of vector databases and search libraries such as Pinecone, Faiss, Chroma […]