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Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

AWS Machine Learning

In this post, we guide you through integrating Amazon Bedrock Agents with enterprise data APIs to create more personalized and effective customer support experiences. An automotive retailer might use inventory management APIs to track stock levels and catalog APIs for vehicle compatibility and specifications.

APIs 130
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GraphStorm 0.3: Scalable, multi-task learning on graphs with user-friendly APIs

AWS Machine Learning

adds new APIs to customize GraphStorm pipelines: you now only need 12 lines of code to implement a custom node classification training loop. Based on customer feedback for the experimental APIs we released in GraphStorm 0.2, introduces refactored graph ML pipeline APIs. Specifically, GraphStorm 0.3 In addition, GraphStorm 0.3

APIs 118
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Generate training data and cost-effectively train categorical models with Amazon Bedrock

AWS Machine Learning

We suggest consulting LLM prompt engineering documentation such as Anthropic prompt engineering for experiments. In the following sections, we provide a detailed explanation on how to construct your first prompt, and then gradually improve it to consistently achieve over 90% accuracy. client = boto3.client("bedrock-runtime",

Education 112
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Enhancing LLM Capabilities with NeMo Guardrails on Amazon SageMaker JumpStart

AWS Machine Learning

Note: For any considerations of adopting this architecture in a production setting, it is imperative to consult with your company specific security policies and requirements. Colang is purpose-built for simplicity and flexibility, featuring fewer constructs than typical programming languages, yet offering remarkable versatility.

Chatbots 114
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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
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Reinvent personalization with generative AI on Amazon Bedrock using task decomposition for agentic workflows

AWS Machine Learning

We present our solution through a fictional consulting company, OneCompany Consulting, using automatically generated personalized website content for accelerating business client onboarding for their consultancy service. Pre-Construction Services - Feasibility Studies - Site Selection and Evaluation.

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What Timeframe for an AI Chatbot Project?

Inbenta

From our experience, it is the framing phase that is the most time-consuming as you have to consult with all the teams involved in the project and obtain various approvals to start the developments. Lack of recommendations on poorly constructed decision trees. How long does it take to deploy an AI chatbot? Poor technical documentation.

Chatbots 140