Remove Artificial Intelligence Remove Lambda Remove Machine Learning
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Build a video insights and summarization engine using generative AI with Amazon Bedrock

AWS Machine Learning - AI

This engine uses artificial intelligence (AI) and machine learning (ML) services and generative AI on AWS to extract transcripts, produce a summary, and provide a sentiment for the call. You can invoke Lambda functions from over 200 AWS services and software-as-a-service (SaaS) applications.

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

When API Gateway receives the request, it triggers an AWS Lambda The Lambda function sends the question to the classifier LLM to determine whether it is a history or math question. These embeddings are then saved as a reference index inside an in-memory FAISS vector store, which is deployed as a Lambda layer.

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

AWS Machine Learning - AI

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. Amazon S3 invokes the {stack_name}-create-batch-queue-{AWS-Region} Lambda function.

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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. Alternatively, you can use AWS Lambda and implement your own logic, or use open source tools such as fmeval. For example, in one common scenario with Cognito that accesses resources with API Gateway and Lambda with a user pool.

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Track, allocate, and manage your generative AI cost and usage with Amazon Bedrock

AWS Machine Learning - AI

Lambda-based Method: This approach uses AWS Lambda as an intermediary between the calling client and the ResourceGroups API. This method employs Lambda Extensions core with an in-memory cache, potentially reducing the number of API calls to ResourceGroups. Dhawal Patel is a Principal Machine Learning Architect at AWS.

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Empower your generative AI application with a comprehensive custom observability solution

AWS Machine Learning - AI

The CloudFormation template provisions resources such as Amazon Data Firehose delivery streams, AWS Lambda functions, Amazon S3 buckets, and AWS Glue crawlers and databases. She leads machine learning projects in various domains such as computer vision, natural language processing, and generative AI.

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Transcribe, translate, and summarize live streams in your browser with AWS AI and generative AI services

AWS Machine Learning - AI

The solution also uses Amazon Cognito user pools and identity pools for managing authentication and authorization of users, Amazon API Gateway REST APIs, AWS Lambda functions, and an Amazon Simple Storage Service (Amazon S3) bucket. To launch the solution in a different Region, change the aws_region parameter accordingly.