Detect hallucinations for RAG-based systems

Favorite With the rise of generative AI and knowledge extraction in AI systems, Retrieval Augmented Generation (RAG) has become a prominent tool for enhancing the accuracy and reliability of AI-generated responses. RAG is as a way to incorporate additional data that the large language model (LLM) was not trained on.

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Shared by AWS Machine Learning May 17, 2025

Vxceed secures transport operations with Amazon Bedrock

Favorite Vxceed delivers SaaS solutions across industries such as consumer packaged goods (CPG), transportation, and logistics. Its modular environments include Lighthouse for CPG demand and supply chains, GroundCentric247 for airline and airport operations, and LimoConnect247 and FleetConnect247 for passenger transport. These solutions support a wide range of customers, including government

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Shared by AWS Machine Learning May 16, 2025

How Apoidea Group enhances visual information extraction from banking documents with multimodal models using LLaMA-Factory on Amazon SageMaker HyperPod

Favorite This post is co-written with Ken Tsui, Edward Tsoi and Mickey Yip from Apoidea Group. The banking industry has long struggled with the inefficiencies associated with repetitive processes such as information extraction, document review, and auditing. These tasks, which require significant human resources, slow down critical operations such as

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Shared by AWS Machine Learning May 16, 2025

Build a financial research assistant using Amazon Q Business and Amazon QuickSight for generative AI–powered insights

Favorite According to a Gartner survey in 2024, 58% of finance functions have adopted generative AI, marking a significant rise in adoption. Among these, four primary use cases have emerged as especially prominent: intelligent process automation, anomaly detection, analytics, and operational assistance. In this post, we show you how Amazon

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Shared by AWS Machine Learning May 15, 2025