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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

This strategy results in more robust, versatile, and efficient applications that better serve diverse user needs and business objectives. We then explore strategies for implementing effective multi-LLM routing in these applications, discussing the key factors that influence the selection and implementation of such strategies.

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Architecting for Resilience: Strategies for Fault-Tolerant Systems

Dzone - DevOps

We'll also discuss core principles and strategies for building fault-tolerant systems. Finally, we'll talk about the future of resilient system design. Emerging trends like cloud computing, containers, and serverless platforms are changing how resilient systems are built.

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Journey to Event Driven – Part 3: The Affinity Between Events, Streams and Serverless

Confluent

With serverless being all the rage, it brings with it a tidal change of innovation. or invest in a vendor-agnostic layer like the serverless framework ? or invest in a vendor-agnostic layer like the serverless framework ? What is more, as the world adopts the event-driven streaming architecture, how does it fit with serverless?

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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.

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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. Splitting document pages Verisk tested multiple strategies for document splitting.

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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. The architecture decouples the client from the server by using streamable HTTP as the transport layer.

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High-performance computing on AWS

Xebia

It’s built on serverless services (API Gateway / Lambda) and provides the same functionality as the CLI tool pcluster. Scheduling parallel jobs There are multiple strategies to schedule parallel jobs, the most convenient way is to use job arrays in sbatch. This is a serverless web UI that mirrors the pcluster functionality.

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