responses

In: Artificial Intelligence

This post is co-written with Abhinav Pandey from Nippon Life India Asset Management Ltd. Accurate information retrieval through generative AI-powered assistants is a popular use case for enterprises. To reduce hallucination and improve overall accuracy, Retrieval Augmented Generation (RAG) remains the most commonly used method to retrieve reliable and accurateContinue Reading

In: Artificial Intelligence

Improving response quality for user queries is essential for AI-driven applications, especially those focusing on user satisfaction. For example, an HR chat-based assistant should strictly follow company policies and respond using a certain tone. A deviation from that can be corrected by feedback from users. This post demonstrates how AmazonContinue Reading

In: Artificial Intelligence

In the rapidly evolving landscape of artificial intelligence, Retrieval Augmented Generation (RAG) has emerged as a game-changer, revolutionizing how Foundation Models (FMs) interact with organization-specific data. As businesses increasingly rely on AI-powered solutions, the need for accurate, context-aware, and tailored responses has never been more critical. Enter the powerful trioContinue Reading