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

AWS Machine Learning Blog

However, as the reach of live streams expands globally, language barriers and accessibility challenges have emerged, limiting the ability of viewers to fully comprehend and participate in these immersive experiences. The extension delivers a web application implemented using the AWS SDK for JavaScript and the AWS Amplify JavaScript library.

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Build an end-to-end RAG solution using Knowledge Bases for Amazon Bedrock and the AWS CDK

AWS Machine Learning Blog

This post demonstrates how to seamlessly automate the deployment of an end-to-end RAG solution using Knowledge Bases for Amazon Bedrock and the AWS Cloud Development Kit (AWS CDK), enabling organizations to quickly set up a powerful question answering system. The AWS CDK already set up. txt,md,html,doc/docx,csv,xls/.xlsx,pdf).

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Accelerate custom labeling workflows in Amazon SageMaker Ground Truth without using AWS Lambda

AWS Machine Learning Blog

Previously, setting up a custom labeling job required specifying two AWS Lambda functions: a pre-annotation function, which is run on each dataset object before it’s sent to workers, and a post-annotation function, which is run on the annotations of each dataset object and consolidates multiple worker annotations if needed.

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Simple guide to training Llama 2 with AWS Trainium on Amazon SageMaker

AWS Machine Learning Blog

Llama2 by Meta is an example of an LLM offered by AWS. Llama 2 is an auto-regressive language model that uses an optimized transformer architecture and is intended for commercial and research use in English. Virginia) and US West (Oregon) AWS Regions, and most recently announced general availability in the US East (Ohio) Region.

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Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 1

AWS Machine Learning Blog

FL doesn’t require moving or sharing data across sites or with a centralized server during the model training process. In this two-part series, we demonstrate how you can deploy a cloud-based FL framework on AWS. Participants can either choose to maintain their data in their on-premises systems or in an AWS account that they control.

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Use zero-shot large language models on Amazon Bedrock for custom named entity recognition

AWS Machine Learning Blog

Some examples include extracting players and positions in an NFL game summary, products mentioned in an AWS keynote transcript, or key names from an article on a favorite tech company. This process must be repeated for every new document and entity type, making it impractical for processing large volumes of documents at scale.

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Create a next generation chat assistant with Amazon Bedrock, Amazon Connect, Amazon Lex, LangChain, and WhatsApp

AWS Machine Learning Blog

The solution’s scalability quickly accommodates growing data volumes and user queries thanks to AWS serverless offerings. It also uses the robust security infrastructure of AWS to maintain data privacy and regulatory compliance. Amazon API Gateway routes the incoming message to the inbound message handler, executed on AWS Lambda.

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