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Track LLM model evaluation using Amazon SageMaker managed MLflow and FMEval

AWS Machine Learning

Rigorous testing allows us to understand an LLMs capabilities, limitations, and potential biases, and provide actionable feedback to identify and mitigate risk. It functions as a standalone HTTP server that provides various REST API endpoints for monitoring, recording, and visualizing experiment runs.

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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. To help you get started with the new API, we have published two Jupyter notebook examples: one for node classification, and one for a link prediction task. Specifically, GraphStorm 0.3

APIs 118
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Alida gains deeper understanding of customer feedback with Amazon Bedrock

AWS Machine Learning

Alida helps the world’s biggest brands create highly engaged research communities to gather feedback that fuels better customer experiences and product innovation. Open-ended survey questions allow responders to provide context and unanticipated feedback. Programmatically using the Amazon Bedrock API and SDKs.

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Orchestrate generative AI workflows with Amazon Bedrock and AWS Step Functions

AWS Machine Learning

Cloud providers have recognized the need to offer model inference through an API call, significantly streamlining the implementation of AI within applications. Although a single API call can address simple use cases, more complex ones may necessitate the use of multiple calls and integrations with other services.

APIs 100
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Product News – May 2023

Lumoa

Lumoa Product News for May 2023 Hey everyone! Keyword suggestions is Lumoa’s way of helping you improve your Topics , as new feedback comes into your account. Exporting detailed feedback. The post Product News – May 2023 appeared first on Lumoa. Lovely seeing you again, back with more exciting Lumoa updates!

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Medical content creation in the age of generative AI

AWS Machine Learning

This is accomplished through an automated revision functionality, which allows the user to interact and send instructions and comments directly to the LLM via an interactive feedback loop. In step 3, the frontend sends the HTTPS request via the WebSocket API and API gateway and triggers the first Amazon Lambda function.

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Unlock the power of structured data for enterprises using natural language with Amazon Q Business

AWS Machine Learning

You can simply ask questions like “What were the sales for outdoor gear in Q3 2023?” Based on the user’s natural language query, the application formulates relevant prompts and metadata, which are then submitted to the chat_sync API of Amazon Q Business. The sample dataset used in this post is from 2023.