Deck Detail: The Batch Newsletter - We Need Better Evals for LLM Applications

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Description: Andrew Ng discusses the challenges of evaluating generative AI applications, especially those producing free-form text. While standardized tests exist for general-purpose models, evaluating specific applications remains difficult and costly. He also highlights RAPTOR, a new retrieval system by Stanford researchers that enhances Retrieval-Augmented Generation (RAG) by summarizing and clustering text for better context within input limits. RAPTOR shows promising results, improving performance while optimizing for cost and input length constraints.
Authors: Andrew Ng
Date Created: 5/31/2024
Last Updated: 5/31/2024
# Flashcards: 7
Tags: AI Agents, Machine Learning