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Getting started with computer use in Amazon Bedrock Agents

AWS Machine Learning

Traditional automation approaches require custom API integrations for each application, creating significant development overhead. In this post, we create a computer use agent demo that provides the critical orchestration layer that transforms computer use from a perception capability into actionable automation.

APIs 135
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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning

Building cloud infrastructure based on proven best practices promotes security, reliability and cost efficiency. We demonstrate how to harness the power of LLMs to build an intelligent, scalable system that analyzes architecture documents and generates insightful recommendations based on AWS Well-Architected best practices.

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Using natural language in Amazon Q Business: From searching and creating ServiceNow incidents and knowledge articles to generating insights

AWS Machine Learning

Although were using admin privileges for the purpose of this post, its a security best practice to apply least privilege permissions and grant only the permissions required to perform a task. This involves creating an OAuth API endpoint in ServiceNow and using the web experience URL from Amazon Q Business as the callback URL.

APIs 97
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Protect sensitive data in RAG applications with Amazon Bedrock

AWS Machine Learning

For more information, see Redacting PII entities with asynchronous jobs (API). The high-level steps are as follows: For our demo , we use a web application UI built using Streamlit. The query is then forwarded using a REST API call to an Amazon API Gateway endpoint along with the access tokens in the header.

APIs 97
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Your guide to generative AI and ML at AWS re:Invent 2024

AWS Machine Learning

As attendees circulate through the GAIZ, subject matter experts and Generative AI Innovation Center strategists will be on-hand to share insights, answer questions, present customer stories from an extensive catalog of reference demos, and provide personalized guidance for moving generative AI applications into production.

APIs 108
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Enterprise-grade natural language to SQL generation using LLMs: Balancing accuracy, latency, and scale

AWS Machine Learning

This work extends upon the post Generating value from enterprise data: Best practices for Text2SQL and generative AI. The end-user sends their natural language queries to the NL2SQL solution using a REST API. Amazon API Gateway is used to provision the REST API, which can be secured by Amazon Cognito.

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Enhance speech synthesis and video generation models with RLHF using audio and video segmentation in Amazon SageMaker

AWS Machine Learning

This setup follows AWS best practices for least-privilege access, making sure CloudFront can only access the specific UI files needed for the annotation interface. Programmatic setup Alternatively, you can create your labeling job programmatically using the CreateLabelingJob API.

APIs 103