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Build and deploy a UI for your generative AI applications with AWS and Python

AWS Machine Learning - AI

Traditionally, building frontend and backend applications has required knowledge of web development frameworks and infrastructure management, which can be daunting for those with expertise primarily in data science and machine learning. Access to Amazon Bedrock foundation models is not granted by default. Choose Create user.

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Amazon Bedrock Flows is now generally available with enhanced safety and traceability

AWS Machine Learning - AI

Reduced time and effort in testing and deploying AI workflows with SDK APIs and serverless infrastructure. We can also quickly integrate flows with our applications using the SDK APIs for serverless flow execution — without wasting time in deployment and infrastructure management.

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Video security analysis for privileged access management using generative AI and Amazon Bedrock

AWS Machine Learning - AI

Operating systems like Windows are predominantly interacted with through a graphical user interface, restricting the PAM system to capturing the activity in these privileged access sessions as video recordings of the server console. The Windows Server desktop is displayed. The following are examples: Here is an example.

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Deploy DeepSeek-R1 Distilled Llama models in Amazon Bedrock

AWS Machine Learning - AI

Amazon Bedrock Custom Model Import enables the import and use of your customized models alongside existing FMs through a single serverless, unified API. This serverless approach eliminates the need for infrastructure management while providing enterprise-grade security and scalability.

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How Cato Networks uses Amazon Bedrock to transform free text search into structured GraphQL queries

AWS Machine Learning - AI

With the Amazon Bedrock serverless experience, you can get started quickly, privately customize FMs with your own data, and quickly integrate and deploy them into your applications using AWS tools without having to manage the infrastructure. This context is augmented to the original query.

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Pixtral Large is now available in Amazon Bedrock

AWS Machine Learning - AI

AWS is the first major cloud provider to deliver Pixtral Large as a fully managed, serverless model. A distinguishing feature of Pixtral Large is its expansive context window of 128,000 tokens, enabling it to simultaneously process multiple images alongside extensive textual data.

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Build an AI-powered document processing platform with open source NER model and LLM on Amazon SageMaker

AWS Machine Learning - AI

Designed with a serverless, cost-optimized architecture, the platform provisions SageMaker endpoints dynamically, providing efficient resource utilization while maintaining scalability. Cost and Performance The solution achieves remarkable throughput by processing 100,000 documents within a 12-hour window.