Remove Experimentation Remove Risk Management Remove Testing
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What Is Model Risk Management and How is it Supported by Enterprise MLOps?

Domino Data Lab

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management.

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6 enterprise DevOps mistakes to avoid

CIO Business Intelligence

But continuous deployment isn’t always appropriate for your business , stakeholders don’t always understand the costs of implementing robust continuous testing , and end-users don’t always tolerate frequent app deployments during peak usage. CrowdStrike recently made the news about a failed deployment impacting 8.5

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AI incident reporting shortcomings leave regulatory safety hole

CIO Business Intelligence

Veera Siivonen, CCO and partner at Saidot, argued for a “balance between regulation and innovation, providing guardrails without narrowing the industry’s potential for experimentation” with the development of artificial intelligence technologies.

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5 Tips to Stay Competitive as AI Technology Evolves

Smart Data Collective

AI technology moves innovation forward by boosting tinkering and experimentation, accelerating the innovation process. It also allows companies to experiment with new concepts and ideas in different ways without relying only on lab tests. Here’s how to stay competitive as technology evolves. Leverage innovation.

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3 key digital transformation priorities for 2024

CIO Business Intelligence

If CIOs don’t improve conversions from pilot to production, they may find their investors losing patience in the process and culture of experimentation. In the SANS 2023 DevSecOps Survey , less than 22% of respondents patched and resolved critical security risks and vulnerabilities in under two days.

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3 principles for regulatory-grade large language model application

CIO Business Intelligence

For example, a good result in a single clinical trial may be enough to consider an experimental treatment or follow-on trial but not enough to change the standard of care for all patients with a specific disease. A provider should be able to show a customer or a regulator the test suite that was used to validate each version of the model.

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Generative AI copilots: What’s hype and where to drive results

CIO Business Intelligence

Many other platforms, such as Coveo’s Relative Generative Answering , Quickbase AI , and LaunchDarkly’s Product Experimentation , have embedded virtual assistant capabilities but don’t brand them copilots. Today, top AI-assistant capabilities delivering results include generating code, test cases, and documentation.