Remove AI Development Remove Prompt Engineering Remove Responsible AI
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Considerations for addressing the core dimensions of responsible AI for Amazon Bedrock applications

AWS Machine Learning Blog

The rapid advancement of generative AI promises transformative innovation, yet it also presents significant challenges. Concerns about legal implications, accuracy of AI-generated outputs, data privacy, and broader societal impacts have underscored the importance of responsible AI development.

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Advancing AI trust with new responsible AI tools, capabilities, and resources

AWS Machine Learning Blog

As generative AI continues to drive innovation across industries and our daily lives, the need for responsible AI has become increasingly important. At AWS, we believe the long-term success of AI depends on the ability to inspire trust among users, customers, and society.

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AI sector study: Record growth masks serious challenges

AI News

There is a rising need for workers with new AI-specific skills, such as prompt engineering, that will require retraining and upskilling opportunities. billion investment in AI skills, security, and data centre infrastructure, aiming to procure more than 20,000 of the most advanced GPUs by 2026. “The

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Decoder-Based Large Language Models: A Complete Guide

Unite.AI

Prompt Engineering : The quality and specificity of the input prompt can significantly impact the generated text. Prompt engineering, the art of crafting effective prompts, has emerged as a crucial aspect of leveraging LLMs for various tasks, enabling users to guide the model's generation process and achieve desired outputs.

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

AWS Machine Learning Blog

In this second part, we expand the solution and show to further accelerate innovation by centralizing common Generative AI components. We also dive deeper into access patterns, governance, responsible AI, observability, and common solution designs like Retrieval Augmented Generation. They’re illustrated in the following figure.

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Evaluating RAG applications with Amazon Bedrock knowledge base evaluation

AWS Machine Learning Blog

This post focuses on RAG evaluation with Amazon Bedrock Knowledge Bases, provides a guide to set up the feature, discusses nuances to consider as you evaluate your prompts and responses, and finally discusses best practices. Jesse Manders is a Senior Product Manager on Amazon Bedrock, the AWS Generative AI developer service.

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Top Artificial Intelligence AI Courses by Microsoft

Marktechpost

Microsoft’s AI courses offer comprehensive coverage of AI and machine learning concepts for all skill levels, providing hands-on experience with tools like Azure Machine Learning and Dynamics 365 Commerce.