Remove Metadata Remove Prompt Engineering Remove Responsible AI
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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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IBM watsonx Platform: Compliance obligations to controls mapping

IBM Journey to AI blog

The enhanced metadata supports the matching categories to internal controls and other relevant policy and governance datasets. The platform incorporates the innovative Prompt Lab tool, specifically engineered to streamline prompt engineering processes.

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Evolving Trends in Prompt Engineering for Large Language Models (LLMs) with Built-in Responsible AI…

ODSC - Open Data Science

Evolving Trends in Prompt Engineering for Large Language Models (LLMs) with Built-in Responsible AI Practices Editor’s note: Jayachandran Ramachandran and Rohit Sroch are speakers for ODSC APAC this August 22–23. As LLMs become integral to AI applications, ethical considerations take center stage.

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Top Artificial Intelligence AI Courses from Google

Marktechpost

Inspect Rich Documents with Gemini Multimodality and Multimodal RAG This course covers using multimodal prompts to extract information from text and visual data and generate video descriptions with Gemini. Introduction to Responsible AI This course explains what responsible AI is, its importance, and how Google implements it in its products.

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How 123RF saved over 90% of their translation costs by switching to Amazon Bedrock

AWS Machine Learning Blog

This prompted 123RF to search for a more reliable and affordable solution to enhance multilingual content discovery. This post explores how 123RF used Amazon Bedrock, Anthropic’s Claude 3 Haiku, and a vector store to efficiently translate content metadata, significantly reduce costs, and improve their global content discovery capabilities.

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How Twilio generated SQL using Looker Modeling Language data with Amazon Bedrock

AWS Machine Learning Blog

Twilio’s use case Twilio wanted to provide an AI assistant to help their data analysts find data in their data lake. They used the metadata layer (schema information) over their data lake consisting of views (tables) and models (relationships) from their data reporting tool, Looker , as the source of truth.

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How Deltek uses Amazon Bedrock for question and answering on government solicitation documents

AWS Machine Learning Blog

The embedding representations of text chunks along with related metadata are indexed in OpenSearch Service. In this step, the user asks a question about the ingested documents and expects a response in natural language. join(context) return context The input question is combined with retrieved context to create a prompt.