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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. An enterprise starts by using a framework to formalize its processes and procedures, which gets increasingly difficult as data science programs grow. What Is Model Risk? Types of Model Risk.

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20 issues shaping generative AI strategies today

CIO Business Intelligence

They note, too, that CIOs — being top technologists within their organizations — will be running point on those concerns as companies establish their gen AI strategies. Here’s a rundown of the top 20 issues shaping gen AI strategies today. Douglas Merrill, a partner at management consulting firm McKinsey & Co.,

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3 key digital transformation priorities for 2024

CIO Business Intelligence

This year’s technology darling and other machine learning investments have already impacted digital transformation strategies in 2023 , and boards will expect CIOs to update their AI transformation strategies frequently. As every CIO can attest, the aggregate demand for IT and data capabilities is straining their IT leadership teams.

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PODCAST: Making AI Real – Episode 2: AI enabled Risk Management for FS powered by BRIDGEi2i Watchtower

bridgei2i

Episode 2: AI enabled Risk Management for FS powered by BRIDGEi2i Watchtower. AI enabled Risk Management for FS powered by BRIDGEi2i Watchtower. Today the Chief Risk Officers(CROs) struggle with the critical task of monitoring and assessing key risks in real time and firefight to mitigate any critical issues that arise.

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Selling the C-suite on preemptive IT investments

CIO Business Intelligence

Others include preparation for zero-day attacks, almost anything having to do with data stewardship, as well as IT training and social engineering audits. Here are three strategies for getting it done. When this happens, corporate risk is heightened as preemptive projects get delayed — sometimes for indefinite periods of time.

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CIO insights: What’s next for AI in the enterprise?

CIO Business Intelligence

CIOs are under increasing pressure to deliver AI across their enterprises – a new reality that, despite the hype, requires pragmatic approaches to testing, deploying, and managing the technologies responsibly to help their organizations work faster and smarter. The top brass is paying close attention. Artificial Intelligence

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Generative AI use cases for the enterprise

IBM Big Data Hub

Demystifying generative AI At the heart of Generative AI lie massive databases of texts, images, code and other data types. This data is fed into generational models, and there are a few to choose from, each developed to excel at a specific task. Imagine each data point as a glowing orb placed on a vast, multi-dimensional landscape.