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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

Organizations are increasingly using multiple large language models (LLMs) when building generative AI applications. For detailed implementation guidelines and examples of Intelligent Prompt Routing on Amazon Bedrock, see Reduce costs and latency with Amazon Bedrock Intelligent Prompt Routing and prompt caching.

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Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

AWS Machine Learning - AI

Generative AI has transformed customer support, offering businesses the ability to respond faster, more accurately, and with greater personalization. AI agents , powered by large language models (LLMs), can analyze complex customer inquiries, access multiple data sources, and deliver relevant, detailed responses.

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How BQA streamlines education quality reporting using Amazon Bedrock

AWS Machine Learning - AI

This is where intelligent document processing (IDP), coupled with the power of generative AI , emerges as a game-changing solution. Enhancing the capabilities of IDP is the integration of generative AI, which harnesses large language models (LLMs) and generative techniques to understand and generate human-like text.

Education 103
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Accelerating insurance policy reviews with generative AI: Verisk’s Mozart companion

AWS Machine Learning - AI

At the forefront of using generative AI in the insurance industry, Verisks generative AI-powered solutions, like Mozart, remain rooted in ethical and responsible AI use. Security and governance Generative AI is very new technology and brings with it new challenges related to security and compliance.

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Introducing AWS MCP Servers for code assistants (Part 1)

AWS Machine Learning - AI

AWS Cloud Development Kit (AWS CDK) Delivers AWS CDK knowledge with tools for implementing best practices, security configurations with cdk-nag , Powertools for AWS Lambda integration, and specialized constructs for generative AI services. She specializes in Generative AI, distributed systems, and cloud computing.

AWS 119
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Ground truth generation and review best practices for evaluating generative AI question-answering with FMEval

AWS Machine Learning - AI

Generative AI question-answering applications are pushing the boundaries of enterprise productivity. These assistants can be powered by various backend architectures including Retrieval Augmented Generation (RAG), agentic workflows, fine-tuned large language models (LLMs), or a combination of these techniques.

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Asure’s approach to enhancing their call center experience using generative AI and Amazon Q in Quicksight

AWS Machine Learning - AI

Asure anticipated that generative AI could aid contact center leaders to understand their teams support performance, identify gaps and pain points in their products, and recognize the most effective strategies for training customer support representatives using call transcripts. Yasmine Rodriguez, CTO of Asure.