Kiran Matty

Jan 21, 2025 | thenewstack.io | Kiran Matty

Many developers have been using retrieval-augmented generation (RAG) with large-scale context corpus to build GenAI applications and tame problems such as AI hallucinations faced by general-purpose large language models (LLMs). Now long context models are emerging like Gemini with a context window of 2 million tokens,  and its potential benefits make you wonder whether you should ditch RAG altogether.

Jun 24, 2024 | couchbase.com | Chris Latimer |Kiran Matty

For technology leaders and developers, the process of integrating rich, proprietary data into generative AI applications is often filled with challenges. Vector similarity search and retrieval augmented generation are powerful tools to help with this, but one mistake extracting, chunking, or vectorizing your data can mean the difference between an AI agent that performs well and one that frustrates users with poor responses and hallucinations.