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

AWS Machine Learning

The custom Google Chat app, configured for HTTP integration, sends an HTTP request to an API Gateway endpoint. Before processing the request, a Lambda authorizer function associated with the API Gateway authenticates the incoming message. A Business or Enterprise Google Workspace account with access to Google Chat.

APIs 124
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Benchmarking Amazon Nova and GPT-4o models with FloTorch

AWS Machine Learning

These models offer enterprises a range of capabilities, balancing accuracy, speed, and cost-efficiency. Using its enterprise software, FloTorch conducted an extensive comparison between Amazon Nova models and OpenAIs GPT-4o models with the Comprehensive Retrieval Augmented Generation (CRAG) benchmark dataset.

Benchmark 103
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Transcribe, translate, and summarize live streams in your browser with AWS AI and generative AI services

AWS Machine Learning

The solution also uses Amazon Cognito user pools and identity pools for managing authentication and authorization of users, Amazon API Gateway REST APIs, AWS Lambda functions, and an Amazon Simple Storage Service (Amazon S3) bucket. To launch the solution in a different Region, change the aws_region parameter accordingly.

APIs 130
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Secure a generative AI assistant with OWASP Top 10 mitigation

AWS Machine Learning

These steps might involve both the use of an LLM and external data sources and APIs. Agent plugin controller This component is responsible for the API integration to external data sources and APIs. The LLM agent is an orchestrator of a set of steps that might be necessary to complete the desired request.

APIs 109
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Unlocking insights and enhancing customer service: Intact’s transformative AI journey with AWS

AWS Machine Learning

The goal was to refine customer service scripts, provide coaching opportunities for agents, and improve call handling processes. Frontend and API The CQ application offers a robust search interface specially crafted for call quality agents, equipping them with powerful auditing capabilities for call analysis.

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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. We will start by using the SageMaker Studio UI and then by using APIs. To get started, set-up a name for your experiment.

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Build a Multi-Agent System with LangGraph and Mistral on AWS

AWS Machine Learning

By using the power of LLMs and combining them with specialized tools and APIs, agents can tackle complex, multistep tasks that were previously beyond the reach of traditional AI systems. Whenever local database information is unavailable, it triggers an online search using the Tavily API. Its used by the weather_agent() function.

APIs 89