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Your guide to generative AI and ML at AWS re:Invent 2024

AWS Machine Learning

In this session, learn best practices for effectively adopting generative AI in your organization. This session covers best practices for a responsible evaluation. Learn best practices and insider tips to optimize your data science workflow and accelerate your ML journey using the SageMaker Python SDK.

APIs 96
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Elevate customer experience by using the Amazon Q Business custom plugin for New Relic AI

AWS Machine Learning

According to New Relic’s 2024 Observability Forecast , businesses face a median annual downtime of 77 hours from high-impact outages. NR AI responds by analyzing current performance data and comparing it to historical trends and best practices. These outages can cost up to $1.9 million per hour.

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From RAG to fabric: Lessons learned from building real-world RAGs at GenAIIC – Part 2

AWS Machine Learning

The prompt uses XML tags following Anthropic’s Claude best practices. The analyst may ask questions such as “Show me all wells that produced oil on June 1st 2024,” “What well produced the most oil in June 2024?”, or “Plot the monthly oil production for well XZY for 2024.”

APIs 118
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Best practices for building robust generative AI applications with Amazon Bedrock Agents – Part 1

AWS Machine Learning

This two-part series explores best practices for building generative AI applications using Amazon Bedrock Agents. This data provides a benchmark for expected agent behavior, including the interaction with existing APIs, knowledge bases, and guardrails connected with the agent. user id 111 Today: 09/03/2024 Certainly!

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A progress update on our commitment to safe, responsible generative AI

AWS Machine Learning

red teaming) In April 2024, we announced the general availability of Guardrails for Amazon Bedrock and Model Evaluation in Amazon Bedrock to make it easier to introduce safeguards, prevent harmful content, and evaluate models against key safety and accuracy criteria. In February 2024, Amazon joined the U.S.

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The executive’s guide to generative AI for sustainability

AWS Machine Learning

It provides examples of use cases and best practices for using generative AI’s potential to accelerate sustainability and ESG initiatives, as well as insights into the main operational challenges of generative AI for sustainability. Throughout this lifecycle, implementing AWS Well-Architected Framework best practices is recommended.

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

AWS Machine Learning

We also released a comprehensive study of co-training language models (LM) and graph neural networks (GNN) for large graphs with rich text features using the Microsoft Academic Graph (MAG) dataset from our KDD 2024 paper. To address this, with GraphStorm 0.3, Dataset Num. of nodes Num. of edges Num. of node/edge types Num.

APIs 117