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Automate Amazon Bedrock batch inference: Building a scalable and efficient pipeline

AWS Machine Learning - AI

Refer to Supported Regions and models for batch inference for current supporting AWS Regions and models. To address this consideration and enhance your use of batch inference, we’ve developed a scalable solution using AWS Lambda and Amazon DynamoDB.

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Amazon S3 Reference for the Cloud Practitioner

Linux Academy

Amazon S3 is an object storage service that is built to be scalable, high available, secure, and performant. Amazon S3 can also be used by other AWS resources of your choosing, so you can build applications in different services like EC2 and Lambda, and those applications can get access to data from S3 (like images and other files).

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Intelligent healthcare forms analysis with Amazon Bedrock

AWS Machine Learning - AI

Handling large volumes of data, extracting unstructured data from multiple paper forms or images, and comparing it with the standard or reference forms can be a long and arduous process, prone to errors and inefficiencies. The SQS message invokes an AWS Lambda The Lambda function is responsible for processing the new form data.

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Techniques and approaches for monitoring large language models on AWS

AWS Machine Learning - AI

Our proposed architecture provides a scalable and customizable solution for online LLM monitoring, enabling teams to tailor your monitoring solution to your specific use cases and requirements. The file saved on Amazon S3 creates an event that triggers a Lambda function. The function invokes the modules.

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

AWS Machine Learning - AI

Before processing the request, a Lambda authorizer function associated with the API Gateway authenticates the incoming message. After it’s authenticated, the request is forwarded to another Lambda function that contains our core application logic. This request contains the user’s message and relevant metadata.

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CBRE and AWS perform natural language queries of structured data using Amazon Bedrock

AWS Machine Learning - AI

In this post, we describe how CBRE partnered with AWS Prototyping to develop a custom query environment allowing natural language query (NLQ) prompts by using Amazon Bedrock, AWS Lambda , Amazon Relational Database Service (Amazon RDS), and Amazon OpenSearch Service. A Lambda function with business logic invokes the primary Lambda function.

AWS 126
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Build scalable Low-Code backends with Booster

The Agile Monkey

However, these tools may not be suitable for more complex data or situations requiring scalability and robust business logic. In short, Booster is a Low-Code TypeScript framework that allows you to quickly and easily create a backend application in the cloud that is highly efficient, scalable, and reliable. WTF is Booster?