Support for AWS DeepComposer ending soon

Favorite AWS DeepComposer was first introduced during AWS re:Invent 2019 as a fun way for developers to compose music by using generative AI. AWS DeepComposer was the world’s first machine learning (ML)-enabled keyboard for developers to get hands-on—literally—with a musical keyboard and the latest ML techniques to compose their own

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Shared by AWS Machine Learning September 18, 2024

Build RAG-based generative AI applications in AWS using Amazon FSx for NetApp ONTAP with Amazon Bedrock

Favorite The post is co-written with Michael Shaul and Sasha Korman from NetApp. Generative artificial intelligence (AI) applications are commonly built using a technique called Retrieval Augmented Generation (RAG) that provides foundation models (FMs) access to additional data they didn’t have during training. This data is used to enrich the

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Shared by AWS Machine Learning September 18, 2024

Improve RAG performance using Cohere Rerank

Favorite This post is co-written with Pradeep Prabhakaran from Cohere. Retrieval Augmented Generation (RAG) is a powerful technique that can help enterprises develop generative artificial intelligence (AI) apps that integrate real-time data and enable rich, interactive conversations using proprietary data. RAG allows these AI applications to tap into external, reliable

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Shared by AWS Machine Learning September 17, 2024

Open Source AI Definition – Weekly update september 16

Favorite Week 37 summary  Endorse the Open Source AI Definition OSI invites individuals and organizations to endorse the Open Source AI Definition (OSAID). Endorsers will have their name and affiliation listed in the press release for Release Candidate 1 (RC1), which is expected to be finalized by the end of

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Shared by voicesofopensource September 16, 2024

Build ultra-low latency multimodal generative AI applications using sticky session routing in Amazon SageMaker

Favorite Amazon SageMaker is a fully managed machine learning (ML) service. With SageMaker, data scientists and developers can quickly and confidently build, train, and deploy ML models into a production-ready hosted environment. SageMaker provides a broad selection of ML infrastructure and model deployment options to help meet your ML inference

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Shared by AWS Machine Learning September 14, 2024