Several companies and experts are discussing the implementation and benefits of retrieval-augmented generation (RAG) in the field of AI. This technique combines semantic search and text generation to enable AI-powered assistants and chatbots to retrieve data from external sources, enhancing their decision-making capabilities. DataStax, LangChainAI, and NVIDIAAI are among the organizations promoting RAG for building AI-powered solutions. PalantirTech has introduced Ontology Augmented Generation (OAG) as an advancement of RAG, enabling LLMs to utilize not only data but also the logic and actions driving decision-making.
Retrieval Augmented Generation (#RAG) enables generative AI to retrieve data from outside sources. #Palantir's Ontology Augmented Generation (OAG) takes RAG to the next level, enabling LLMs to leverage not only data, but the logic and actions that drive decision-making. https://t.co/fmLF3EZjKX
Register for this #generativeAI webinar to learn how enterprises are building AI-powered assistants and chatbots using retrieval-augmented generation (#RAG) to transform the way their business operates. https://t.co/54zVwcOoUf https://t.co/oxHegSg5Na
Today, our CTO & Co-Founder Nagendra Kumar talks about how to create your own retrieval-augmented generative AI (or RAG) chatbot in Destination CRM. https://t.co/tf5c63bnuR #generativeAI #chatbots
DataStax ❤️ LangChain Learn why we decided to leverage @LangChainAI as the foundation for our retrieval augmented generation (RAG) solution RAGStack. https://t.co/eHAnTOSadU
How to implement a RAG pipeline on NLP Cloud? Retrieval-Augmented Generation (aka "RAG") is an advanced way to perform question answering on a large corpus of texts by mixing semantic search and text generation. Here is how you can achieve it: https://t.co/yQ5bJ1qBiZ #AI
Chat with your #KnowledgeBase within minutes using the @AbacusAI Retrieval Augmented Generation (RAG) technique and fine-tuned #LLMs at: https://t.co/jU8egNJvQA ———— #AI #GenerativeAI #MachineLearning #DeepLearning #Chatbot #BigData #DataScience #DataScientists https://t.co/HLxWBvgAE1