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Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning

Many businesses want to integrate these cutting-edge AI capabilities with their existing collaboration tools, such as Google Chat, to enhance productivity and decision-making processes. The custom Google Chat app, configured for HTTP integration, sends an HTTP request to an API Gateway endpoint.

APIs 124
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Transforming credit decisions using generative AI with Rich Data Co and AWS

AWS Machine Learning

This strategy equipped us to align each task with the most suitable foundation model (FM) and tools. Its equipped with the appropriate FM for the task and the necessary tools to perform actions and access knowledge. Tools Tools extend agent capabilities beyond the FM.

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How Formula 1® uses generative AI to accelerate race-day issue resolution

AWS Machine Learning

During these live events, F1 IT engineers must triage critical issues across its services, such as network degradation to one of its APIs. This impacts downstream services that consume data from the API, including products such as F1 TV, which offer live and on-demand coverage of every race as well as real-time telemetry.

APIs 71
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Unlocking generative AI for enterprises: How SnapLogic powers their low-code Agent Creator using Amazon Bedrock

AWS Machine Learning

Agent Creator is a no-code visual tool that empowers business users and application developers to create sophisticated large language model (LLM) powered applications and agents without programming expertise. The robust capabilities and unified API of Amazon Bedrock make it an ideal foundation for developing enterprise-grade AI applications.

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Building an efficient MLOps platform with OSS tools on Amazon ECS with AWS Fargate

AWS Machine Learning

This tool enables marketers to craft compelling email subject lines that significantly boost open rates and engagement, tailored perfectly to the audience’s preferences and behaviors. To address these challenges, the organization developed an MLOps platform based on four key open-source tools: Airflow, Feast, dbt, and MLflow.

APIs 122
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Reducing hallucinations in LLM agents with a verified semantic cache using Amazon Bedrock Knowledge Bases

AWS Machine Learning

Solution overview Our solution implements a verified semantic cache using the Amazon Bedrock Knowledge Bases Retrieve API to reduce hallucinations in LLM responses while simultaneously improving latency and reducing costs. The function checks the semantic cache (Amazon Bedrock Knowledge Bases) using the Retrieve API.

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Secure Amazon SageMaker Studio presigned URLs Part 3: Multi-account private API access to Studio

AWS Machine Learning

In the post Secure Amazon SageMaker Studio presigned URLs Part 2: Private API with JWT authentication , we demonstrated how to build a private API to generate Amazon SageMaker Studio presigned URLs that are only accessible by an authenticated end-user within the corporate network from a single account.

APIs 98