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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 instance, consider an AI-driven legal document analysis system designed for businesses of varying sizes, offering two primary subscription tiers: Basic and Pro.

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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. Data: Policy forms Mozart is designed to author policy forms like coverage and endorsements.

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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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Automate emails for task management using Amazon Bedrock Agents, Amazon Bedrock Knowledge Bases, and Amazon Bedrock Guardrails

AWS Machine Learning - AI

Amazon Bedrock offers a serverless experience so you can get started quickly, privately customize FMs with your own data, and integrate and deploy them into your applications using AWS tools without having to manage infrastructure. The following diagram provides a detailed view of the architecture to enhance email support using generative AI.

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AWS empowers sales teams using generative AI solution built on Amazon Bedrock

AWS Machine Learning - AI

At AWS, we are transforming our seller and customer journeys by using generative artificial intelligence (AI) across the sales lifecycle. Prospecting, opportunity progression, and customer engagement present exciting opportunities to utilize generative AI, using historical data, to drive efficiency and effectiveness.

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Medical content creation in the age of generative AI

AWS Machine Learning - AI

Generative AI and transformer-based large language models (LLMs) have been in the top headlines recently. These models demonstrate impressive performance in question answering, text summarization, code, and text generation. The imperative for regulatory oversight of large language models (or generative AI) in healthcare.

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How Mixbook used generative AI to offer personalized photo book experiences

AWS Machine Learning - AI

Years ago, Mixbook undertook a strategic initiative to transition their operational workloads to Amazon Web Services (AWS) , a move that has continually yielded significant advantages. The data intake process involves three macro components: Amazon Aurora MySQL-Compatible Edition , Amazon S3, and AWS Fargate for Amazon ECS.