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Amazon Bedrock Custom Model Import now generally available

AWS Machine Learning

This feature empowers customers to import and use their customized models alongside existing foundation models (FMs) through a single, unified API. However, hosting models presents its own unique set of challenges. Having a unified developer experience when accessing custom models or base models through Amazon Bedrock’s API.

APIs 139
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Enhance call center efficiency using batch inference for transcript summarization with Amazon Bedrock

AWS Machine Learning

As the volume of call data grows, traditional analysis methods struggle to keep pace, creating a demand for a scalable solution. Batch inference presents itself as a compelling approach to tackle this challenge. Batch job submission – Initiate and manage batch inference jobs through the Amazon Bedrock console or API.

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Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning

Wipro has used the input filter and join functionality of SageMaker batch transformation API. The response is returned to Lambda and sent back to the application through API Gateway. Evaluate payload – If there is incremental data or payload present for the current run, it invokes the monitoring branch.

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Build an agronomic data platform with Amazon SageMaker geospatial capabilities

AWS Machine Learning

Developing, testing, and improving ML computer vision models that detect clouds and atmospheric issues in satellite imagery presents challenges for builders of agronomic data platforms. These differences in satellite images and frequencies also lead to differences in API capabilities and features.

APIs 87
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Streamline Sales Processes with Enterprise CPQ

Cincom

Integration with Existing Systems: APIs facilitate data sharing between CPQ and other core platforms like CRM, ERP, accounting, e-commerce, and more. Cincom CPQ insights expand deals today and safeguard accounts for tomorrow by empowering reps to proactively present relevant offers tailored to existing clients’ unique needs.

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Reinvent personalization with generative AI on Amazon Bedrock using task decomposition for agentic workflows

AWS Machine Learning

This post presents an automated personalization solution that balances the innovative capabilities of LLMs with adherence to human directives and human-curated assets for a consistent and responsible personalization experience for your customers. For this post, we use Anthropic’s Claude models on Amazon Bedrock.