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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.

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Lambda Calculus Through JavaScript, Part 4

Xebia

This is the fourth post in the Lambda Calculus Through JavaScript series. If you’re just joining us, make sure to go back and start with Lambda calculus through JavaScript, part 1. As usual, we’ll discover that lambda calculus gives us the ingredients to introduce this concept without extending the language, just by translation.

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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.

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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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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. We walk you through our solution, detailing the core logic of the Lambda functions.

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Techniques and approaches for monitoring large language models on AWS

AWS Machine Learning - AI

However, as these models continue to grow in size and complexity, monitoring their performance and behavior has become increasingly challenging. Monitoring the performance and behavior of LLMs is a critical task for ensuring their safety and effectiveness. The file saved on Amazon S3 creates an event that triggers a Lambda function.

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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.