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Amazon has introduced RAGChecker, a new AI tool designed to enhance accuracy in Retrieval-Augmented Generation (RAG) systems. The tool, developed in collaboration with researchers from Amazon AWS AI, Shanghai Jiaotong University, and Westlake University, serves as a fine-grained evaluation framework for diagnosing retrieval and generation modules in RAG systems. Despite its potential to revolutionize AI accuracy, the public availability of RAGChecker remains uncertain.
1/n How Mutual Consistent Reasoning Unlocks Agentic AI for Small Language Models Large Language Models (LLMs) have demonstrated remarkable abilities in various tasks, yet their capacity for complex reasoning remains a significant challenge, especially for their smaller, more… https://t.co/EzUuRh54Jm
1/n How Understanding Stateful Tools Advances Agentic AI The rapid advancement of Large Language Models (LLMs) has ignited a wave of excitement and research into their potential for interacting with and manipulating the world around them. Imagine LLMs not just as eloquent… https://t.co/FdjkSzFbsQ
Using Evaluations to Optimize a RAG Pipeline: from Chunkings and Embeddings to LLMs by @cbergman @TDataScience Learn more: https://t.co/8TAELSOWJs #AI #BigData #ArtificialIntelligence #DataScience #Tech cc: @bernardmarr @ylecun @sallyeaves https://t.co/StMXYgfP62
