Remove Machine Learning Remove Prompt Engineering Remove Responsible AI
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How Travelers Insurance classified emails with Amazon Bedrock and prompt engineering

AWS Machine Learning Blog

Increasingly, FMs are completing tasks that were previously solved by supervised learning, which is a subset of machine learning (ML) that involves training algorithms using a labeled dataset. In some cases, smaller supervised models have shown the ability to perform in production environments while meeting latency requirements.

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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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5 Jobs That Will Use Prompt Engineering in 2023

ODSC - Open Data Science

With that said, companies are now realizing that to bring out the full potential of AI, prompt engineering is a must. So we have to ask, what kind of job now and in the future will use prompt engineering as part of its core skill set?

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Accelerating insurance policy reviews with generative AI: Verisk’s Mozart companion

Flipboard

At the forefront of using generative AI in the insurance industry, Verisks generative AI-powered solutions, like Mozart, remain rooted in ethical and responsible AI use. Prompt optimization The change summary is different than showing differences in text between the two documents.

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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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Streamline grant proposal reviews using Amazon Bedrock

AWS Machine Learning Blog

By combining the advanced NLP capabilities of Amazon Bedrock with thoughtful prompt engineering, the team created a dynamic, data-driven, and equitable solution demonstrating the transformative potential of large language models (LLMs) in the social impact domain. Focus solely on providing the assessment based on the given inputs.