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Introducing multi-turn conversation with an agent node for Amazon Bedrock Flows (preview)

AWS Machine Learning

Amazon Bedrock Flows offers an intuitive visual builder and a set of APIs to seamlessly link foundation models (FMs), Amazon Bedrock features, and AWS services to build and automate user-defined generative AI workflows at scale. Test the flow Youre now ready to test the flow through the Amazon Bedrock console or API.

APIs 129
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Best practices for building secure applications with Amazon Transcribe

AWS Machine Learning

Because these best practices might not be appropriate or sufficient for your environment, use them as helpful considerations rather than prescriptions. Both HTTP/2 and WebSockets streaming connections are established over Transport Layer Security (TLS), which is a widely accepted cryptographic protocol. or later.

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Training large language models on Amazon SageMaker: Best practices

AWS Machine Learning

In this post, we dive into tips and best practices for successful LLM training on Amazon SageMaker Training. The post covers all the phases of an LLM training workload and describes associated infrastructure features and best practices. Some of the best practices in this post refer specifically to ml.p4d.24xlarge

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Image and video prompt engineering for Amazon Nova Canvas and Amazon Nova Reel

AWS Machine Learning

Solution overview To get started with Nova Canvas and Nova Reel, you can either use the Image/Video Playground on the Amazon Bedrock console or access the models through APIs. When writing a video generation prompt for Nova Reel, be mindful of the following requirements and best practices: Prompts must be no longer than 512 characters.

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Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning

Customers can use the SageMaker Studio UI or APIs to specify the SageMaker Model Registry model to be shared and grant access to specific AWS accounts or to everyone in the organization. It also helps achieve data, project, and team isolation while supporting software development lifecycle best practices.

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Achieve operational excellence with well-architected generative AI solutions using Amazon Bedrock

AWS Machine Learning

Because this is an emerging area, best practices, practical guidance, and design patterns are difficult to find in an easily consumable basis. This integration makes sure enterprises can take advantage of the full power of generative AI while adhering to best practices in operational excellence.

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Develop generative AI applications to improve teaching and learning experiences

AWS Machine Learning

Amazon Bedrock is a fully managed service that makes foundation models from leading AI startups and Amazon available via easy-to-use API interfaces. The solution also uses the grammatical error correction API and the paraphrase API from AI21 to recommend word and sentence corrections. The following is the generated image output.

APIs 130