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Serverless, it can help you brew beer

Xebia

How does Serverless help? This allows you to use a Lambda function to use business logic to decide whether the call can be performed. The documentation clearly states that you should not use the usage plans for authentication. Conclusion Real-world examples help illustrate our options for serverless technology.

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Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning - AI

AWS offers powerful generative AI services , including Amazon Bedrock , which allows organizations to create tailored use cases such as AI chat-based assistants that give answers based on knowledge contained in the customers’ documents, and much more. This request contains the user’s message and relevant metadata.

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

AWS Machine Learning - AI

Access to car manuals and technical documentation helps the agent provide additional context for curated guidance, enhancing the quality of customer interactions. The workflow includes the following steps: Documents (owner manuals) are uploaded to an Amazon Simple Storage Service (Amazon S3) bucket.

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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. Meanwhile, the business analysis interface would focus on text summarization for analyzing various business documents. This is illustrated in the following figure.

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AWS Lambda Benchmarking

Xebia

In this blog post, we examine the relative costs of different language runtimes on AWS Lambda. Many languages can be used with AWS Lambda today, so we focus on four interesting ones. Rust just came to AWS Lambda in November 2023 , so probably a lot of folks are wondering whether to try it out. The maximum injection size is 500.

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

We demonstrate how to harness the power of LLMs to build an intelligent, scalable system that analyzes architecture documents and generates insightful recommendations based on AWS Well-Architected best practices. An interactive chat interface allows deeper exploration of both the original document and generated content.

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Amazon Q Business simplifies integration of enterprise knowledge bases at scale

AWS Machine Learning - AI

Large-scale data ingestion is crucial for applications such as document analysis, summarization, research, and knowledge management. These tasks often involve processing vast amounts of documents, which can be time-consuming and labor-intensive. This solution uses the powerful capabilities of Amazon Q Business.