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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 128
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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 116
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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",

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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 87
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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.

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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
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Automate chatbot for document and data retrieval using Agents and Knowledge Bases for Amazon Bedrock

AWS Machine Learning

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

Chatbots 128