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Elevate healthcare interaction and documentation with Amazon Bedrock and Amazon Transcribe using Live Meeting Assistant

AWS Machine Learning

LMA for healthcare is an extended version of the Live Meeting Assistant solution that has been adapted to generate clinical notes automatically during virtual doctor-patient consultations. In the future, we expect LMA for healthcare to use the AWS HealthScribe API in addition to other AWS services.

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Automate caption creation and search for images at enterprise scale using generative AI and Amazon Kendra

AWS Machine Learning

We demonstrate CDE using simple examples and provide a step-by-step guide for you to experience CDE in an Amazon Kendra index in your own AWS account. After ingestion, images can be searched via the Amazon Kendra search console, API, or SDK. However, we can use CDE for a wider range of use cases.

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How Earth.com and Provectus implemented their MLOps Infrastructure with Amazon SageMaker

AWS Machine Learning

By enabling effective management of the ML lifecycle, MLOps can help account for various alterations in data, models, and concepts that the development of real-time image recognition applications is associated with. At-scale, real-time image recognition is a complex technical problem that also requires the implementation of MLOps.

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Implement serverless semantic search of image and live video with Amazon Titan Multimodal Embeddings

AWS Machine Learning

Amazon Bedrock is a fully managed service that provides access to a range of high-performing foundation models from leading AI companies through a single API. The second component converts these extracted frames into vector embeddings directly by calling the Amazon Bedrock API with Amazon Titan Multimodal Embeddings.

APIs 91
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Build a Speech Translation App on Deno With Azure and Vonage

Nexmo

Vonage recently released Automatic Speech Recognition (ASR) as a new feature on the Voice API, which is a great reason to build an entertaining new voice application to leverage this new capability! In this tutorial we will be building utilizing the Microsoft Azure Speech Translation API. A Microsoft Azure Account.

APIs 62
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Dialogue-guided visual language processing with Amazon SageMaker JumpStart

AWS Machine Learning

Their use cases span various domains, from media entertainment to medical diagnostics and quality assurance in manufacturing. The TGI framework underpins the model inference layer, providing RESTful APIs for robust integration and effortless accessibility. amazonaws.com # Build the TGI docker image locally docker build.

APIs 99