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Spend Smarter, Not More: A Guide to AWS Storage Cost Optimization

Xebia

Introduction With an ever-expanding digital universe, data storage has become a crucial aspect of every organization’s IT strategy. S3 Storage Undoubtedly, anyone who uses AWS will inevitably encounter S3, one of the platform’s most popular storage services. Storage Class Designed For Retrieval Change Min.

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Build a video insights and summarization engine using generative AI with Amazon Bedrock

AWS Machine Learning - AI

All of this data is centralized and can be used to improve metrics in scenarios such as sales or call centers. AWS Lambda is an event-driven compute service that lets you run code for virtually any type of application or backend service without provisioning or managing servers.

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Empower your generative AI application with a comprehensive custom observability solution

AWS Machine Learning - AI

Observability refers to the ability to understand the internal state and behavior of a system by analyzing its outputs, logs, and metrics. The CloudFormation template provisions resources such as Amazon Data Firehose delivery streams, AWS Lambda functions, Amazon S3 buckets, and AWS Glue crawlers and databases.

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How BQA streamlines education quality reporting using Amazon Bedrock

AWS Machine Learning - AI

The solution consists of the following steps: Relevant documents are uploaded and stored in an Amazon Simple Storage Service (Amazon S3) bucket. The text extraction AWS Lambda function is invoked by the SQS queue, processing each queued file and using Amazon Textract to extract text from the documents.

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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning - AI

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. Model monitoring – The model monitoring service allows tenants to evaluate model performance against predefined metrics. Alternatively, you can use AWS Lambda and implement your own logic, or use open source tools such as fmeval.

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Techniques and approaches for monitoring large language models on AWS

AWS Machine Learning - AI

In this post, we demonstrate a few metrics for online LLM monitoring and their respective architecture for scale using AWS services such as Amazon CloudWatch and AWS Lambda. Overview of solution The first thing to consider is that different metrics require different computation considerations. The function invokes the modules.

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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

Using Amazon Bedrock allows for iteration of the solution using knowledge bases for simple storage and access of call transcripts as well as guardrails for building responsible AI applications. This step is shown by business analysts interacting with QuickSight in the storage and visualization step through natural language.