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Global AI regulations: Beyond the U.S. and Europe

CIO

Second, some countries such as the United Arab Emirates (UAE) have implemented sector-specific AI requirements while allowing other sectors to follow voluntary guidelines. The G7 collection of nations has also proposed a voluntary AI code of conduct. Similar voluntary guidance can be seen in Singapore and Japan.

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

AWS Machine Learning - AI

Through advanced data analytics, software, scientific research, and deep industry knowledge, Verisk helps build global resilience across individuals, communities, and businesses. Verisk has a governance council that reviews generative AI solutions to make sure that they meet Verisks standards of security, compliance, and data use.

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How AI continues to reshape the cybersecurity arsenal

CIO

This necessitates continuous adaptation and innovation across various verticals, from data management and cybersecurity to software development and user experience design. Source code analysis tools Static application security testing (SAST) is one of the most widely used cybersecurity tools worldwide. SAST is no different.

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How to know a business process is ripe for agentic AI

CIO

Does [it] have in place thecompliance review and monitoring structure to initially evaluate the risks of the specific agentic AI; monitor and correct where issues arise; measure success; remain up to date on applicable law and regulation? Feaver says.

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EBSCOlearning scales assessment generation for their online learning content with generative AI

AWS Machine Learning - AI

The goal was ambitious: to create an automated solution that could produce high-quality, multiple-choice questions at scale, while adhering to strict guidelines on bias, safety, relevance, style, tone, meaningfulness, clarity, and diversity, equity, and inclusion (DEI). Sonnet model in Amazon Bedrock.

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For successful AI projects, celebrate your graveyard and be prepared to fail fast

TechCrunch

AI teams invest a lot of rigor in defining new project guidelines. In the absence of clear guidelines, teams let infeasible projects drag on for months. They put up a dog and pony show during project review meetings for fear of becoming the messengers of bad news. AI projects are different from traditional software projects.

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Model customization, RAG, or both: A case study with Amazon Nova

AWS Machine Learning - AI

In this post, we seek to address this growing need by offering clear, actionable guidelines and best practices on when to use each approach, helping you make informed decisions that align with your unique requirements and objectives. On the Review and create page, review the settings and choose Create Knowledge Base.