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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

For instance, consider an AI-driven legal document analysis system designed for businesses of varying sizes, offering two primary subscription tiers: Basic and Pro. This specialized LLM, which can be trained on nuanced distinctions within its domain, can then determine crucial factors such as task complexity or urgency.

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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

Key challenges include the need for ongoing training for support staff, difficulties in managing and retrieving scattered information, and maintaining consistency across different agents’ responses. Solution overview This section outlines the architecture designed for an email support system using generative AI.

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Creating asynchronous AI agents with Amazon Bedrock

AWS Machine Learning - AI

Much like traditional business process automation through technology, the agentic AI architecture is the design of AI systems designed to resolve complex problems with limited or indirect human intervention. Agent broker architecture Messages sent to EventBridge are routed through an EventBridge rule to Lambda.

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Extend large language models powered by Amazon SageMaker AI using Model Context Protocol

AWS Machine Learning - AI

By doing this, clients and servers can scale independently, making it a great fit for serverless orchestration powered by Lambda, AWS Fargate for Amazon ECS, or Fargate for Amazon EKS. For example, a simple way to deploy an MCP server is to use Lambda support for Docker images to install the MCP dependency on the Lambda function or Fargate.

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New live online training courses

O'Reilly Media - Ideas

Get hands-on training in Docker, microservices, cloud native, Python, machine learning, and many other topics. Learn new topics and refine your skills with more than 219 new live online training courses we opened up for June and July on the O'Reilly online learning platform. Systems Design for Site Reliability Engineers , August 7.

Course 93
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Medical content creation in the age of generative AI

AWS Machine Learning - AI

The solution has been designed using the following services: Amazon Elastic Container Service (ECS) : to deploy and manage our Streamlit UI. Amazon Lambda : to run the backend code, which encompasses the generative logic. In step 5, the lambda function triggers the Amazon Textract to parse and extract data from pdf documents.

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

AWS Machine Learning - AI

During the solution design process, Verisk also considered using Amazon Bedrock Knowledge Bases because its purpose built for creating and storing embeddings within Amazon OpenSearch Serverless. In the future, Verisk intends to use the Amazon Titan Embeddings V2 model. The user can pick the two documents that they want to compare.