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Amazon Bedrock launches Session Management APIs for generative AI applications (Preview)

AWS Machine Learning

Amazon Bedrock announces the preview launch of Session Management APIs, a new capability that enables developers to simplify state and context management for generative AI applications built with popular open source frameworks such as LangGraph and LlamaIndex. Building generative AI applications requires more than model API calls.

APIs 121
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7 Reasons ChatGPT Alone Can’t Deliver the Customer Service You Need

CCNG

Unclear ROI ChatGPT is currently not accessible via API and the cost of a (hypythetical) API call are unclear. However while there is no publicly available data on the cost of ChatGPT, one estimate puts it in the millions of dollars per month. Its not as automated as people assume.

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Implement human-in-the-loop confirmation with Amazon Bedrock Agents

AWS Machine Learning

In addition, they use the developer-provided instruction to create an orchestration plan and then carry out the plan by invoking company APIs and accessing knowledge bases using Retrieval Augmented Generation (RAG) to provide an answer to the users request. This differs from confirmation flows where the agent directly executes API calls.

APIs 120
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Build generative AI applications quickly with Amazon Bedrock IDE in Amazon SageMaker Unified Studio

AWS Machine Learning

This includes setting up Amazon API Gateway , AWS Lambda functions, and Amazon Athena to enable querying the structured sales data. Navigate to the AWS Secrets Manager console and find the secret -api-keys. Expected response: Based on the customer reviews and feedback, the sentiment surrounding our Office Supplies products is mixed.

APIs 107
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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. API Gateway is serverless and hence automatically scales with traffic. API Gateway also provides a WebSocket API. Incoming requests to the gateway go through this point.

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Empower your generative AI application with a comprehensive custom observability solution

AWS Machine Learning

Observability empowers you to proactively monitor and analyze your generative AI applications, and evaluation helps you collect feedback, refine models, and enhance output quality. In the context of Amazon Bedrock , observability and evaluation become even more crucial.

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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 GraphStorm 0.3

APIs 118