Index your Atlassian Confluence Cloud contents using the Amazon Q Confluence Cloud connector for Amazon Q Business

Favorite Amazon Q Business is a generative artificial intelligence (AI)-powered assistant designed to enhance enterprise operations. It’s a fully managed service that helps provide accurate answers to users’ questions while honoring the security and access restrictions of the content. It can be tailored to your specific business needs by connecting

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Shared by AWS Machine Learning August 23, 2024

Unleashing the power of generative AI: Verisk’s Discovery Navigator revolutionizes medical record review

Favorite This post is co-written with Sneha Godbole and Kate Riordan from Verisk. Verisk (Nasdaq: VRSK) is a leading strategic data analytics and technology partner to the global insurance industry. It empowers its customers to strengthen operating efficiency, improve underwriting and claims outcomes, combat fraud, and make informed decisions about

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Shared by AWS Machine Learning August 23, 2024

Build private and secure enterprise generative AI applications with Amazon Q Business using IAM Federation

Favorite Amazon Q Business is a conversational assistant powered by generative artificial intelligence (AI) that enhances workforce productivity by answering questions and completing tasks based on information in your enterprise systems, which each user is authorized to access. In an earlier post, we discussed how you can build private and

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Shared by AWS Machine Learning August 23, 2024

Elevate healthcare interaction and documentation with Amazon Bedrock and Amazon Transcribe using Live Meeting Assistant

Favorite Today, physicians spend about 49% of their workday documenting clinical visits, which impacts physician productivity and patient care. Did you know that for every eight hours that office-based physicians have scheduled with patients, they spend more than five hours in the EHR? As a consequence, healthcare practitioners exhibit a

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Shared by AWS Machine Learning August 22, 2024

Accuracy evaluation framework for Amazon Q Business

Favorite Generative artificial intelligence (AI), particularly Retrieval Augmented Generation (RAG) solutions, are rapidly demonstrating their vast potential to revolutionize enterprise operations. RAG models combine the strengths of information retrieval systems with advanced natural language generation, enabling more contextually accurate and informative outputs. From automating customer interactions to optimizing backend operation

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Shared by AWS Machine Learning August 22, 2024

Analyze customer reviews using Amazon Bedrock

Favorite Customer reviews can reveal customer experiences with a product and serve as an invaluable source of information to the product teams. By continually monitoring these reviews over time, businesses can recognize changes in customer perceptions and uncover areas of improvement. Analyzing these reviews to extract actionable insights enables data-driven

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Shared by AWS Machine Learning August 22, 2024

Fine-tune Meta Llama 3.1 models for generative AI inference using Amazon SageMaker JumpStart

Favorite Fine-tuning Meta Llama 3.1 models with Amazon SageMaker JumpStart enables developers to customize these publicly available foundation models (FMs). The Meta Llama 3.1 collection represents a significant advancement in the field of generative artificial intelligence (AI), offering a range of capabilities to create innovative applications. The Meta Llama 3.1

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Shared by AWS Machine Learning August 22, 2024

Enhance call center efficiency using batch inference for transcript summarization with Amazon Bedrock

Favorite Today, we are excited to announce general availability of batch inference for Amazon Bedrock. This new feature enables organizations to process large volumes of data when interacting with foundation models (FMs), addressing a critical need in various industries, including call center operations. Call center transcript summarization has become an

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Shared by AWS Machine Learning August 22, 2024