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Transcribe, translate, and summarize live streams in your browser with AWS AI and generative AI services

AWS Machine Learning Blog

However, as the reach of live streams expands globally, language barriers and accessibility challenges have emerged, limiting the ability of viewers to fully comprehend and participate in these immersive experiences. The extension delivers a web application implemented using the AWS SDK for JavaScript and the AWS Amplify JavaScript library.

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Implement RAG while meeting data residency requirements using AWS hybrid and edge services

Flipboard

With the general availability of Amazon Bedrock Agents , you can rapidly develop generative AI applications to run multi-step tasks across a myriad of enterprise systems and data sources.

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Principal Financial Group uses QnABot on AWS and Amazon Q Business to enhance workforce productivity with generative AI

AWS Machine Learning Blog

With the QnABot on AWS (QnABot), integrated with Microsoft Azure Entra ID access controls, Principal launched an intelligent self-service solution rooted in generative AI. Principal sought to develop natural language processing (NLP) and question-answering capabilities to accurately query and summarize this unstructured data at scale.

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Top 10 AI and Data Science Trends in 2022

Analytics Vidhya

Deep learning, natural language processing, and computer vision are examples […]. The post Top 10 AI and Data Science Trends in 2022 appeared first on Analytics Vidhya. Times change, technology improves and our lives get better.

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Amazon Q Business simplifies integration of enterprise knowledge bases at scale

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In this new era of emerging AI technologies, we have the opportunity to build AI-powered assistants tailored to specific business requirements. For complex customer issues, the process was especially time-consuming, laborious, and at times extended the wait time for customers seeking resolutions.

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Improving Retrieval Augmented Generation accuracy with GraphRAG

AWS Machine Learning Blog

Customers need better accuracy to take generative AI applications into production. To address this, customers often begin by enhancing generative AI accuracy through vector-based retrieval systems and the Retrieval Augmented Generation (RAG) architectural pattern, which integrates dense embeddings to ground AI outputs in relevant context.

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Advancing AI trust with new responsible AI tools, capabilities, and resources

AWS Machine Learning Blog

As generative AI continues to drive innovation across industries and our daily lives, the need for responsible AI has become increasingly important. At AWS, we believe the long-term success of AI depends on the ability to inspire trust among users, customers, and society.

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