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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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How can you measure customer satisfaction?

ViiBE Blog

Automotive , Construction , Energy , Insurance , Retail , SMB , Transport. Consequently, detractors are unsatisfied customers who may potentially damage the company’s name, brand image, and future growth through spreading bad feedback. Customer satisfaction measurement: best practices. ViiBE Blog. Natalia Barszcz.

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'Simple Sticker' Idea: Transform Your Customer Experience Today

PeopleMetrics

My only mode of transportation. “We really appreciate and value customer feedback.” Read our 7 Practices of a Customer Centric Organization for some best practices to implement in your own company. The feeling that I had for the remainder of the weekend was indescribable. I felt unsafe, violated, angry.

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Achieve operational excellence with well-architected generative AI solutions using Amazon Bedrock

AWS Machine Learning

Because this is an emerging area, best practices, practical guidance, and design patterns are difficult to find in an easily consumable basis. This integration makes sure enterprises can take advantage of the full power of generative AI while adhering to best practices in operational excellence.

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Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning

It also helps achieve data, project, and team isolation while supporting software development lifecycle best practices. You can leave feedback in the comments section. Multi-account architecture for sharing models A multi-account strategy improves security, scalability, and reliability of your systems.

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Develop generative AI applications to improve teaching and learning experiences

AWS Machine Learning

When students provide answers, the solution provides real-time assessments and offers personalized feedback and guidance for students to improve their answers. For our example, a teacher inputs the Kids and Bicycle Safety guidelines from the United States Department of Transportation. The following is the generated image output.

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Advanced RAG patterns on Amazon SageMaker

AWS Machine Learning

A number of techniques are typically used to improve the accuracy and performance of an LLM’s output, such as fine-tuning with parameter efficient fine-tuning (PEFT) , reinforcement learning from human feedback (RLHF) , and performing knowledge distillation.