Remove Experimentation Remove Metrics Remove Risk Remove Risk Management
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10 Technical Blogs for Data Scientists to Advance AI/ML Skills

DataRobot Blog

Other organizations are just discovering how to apply AI to accelerate experimentation time frames and find the best models to produce results. Taking a Multi-Tiered Approach to Model Risk Management. Data scientists are in demand: the U.S. Explore these 10 popular blogs that help data scientists drive better data decisions.

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7 steps for turning shadow IT into a competitive edge

CIO Business Intelligence

Ask IT leaders about their challenges with shadow IT, and most will cite the kinds of security, operational, and integration risks that give shadow IT its bad rep. That’s not to downplay the inherent risks of shadow IT.

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How to become an AI+ enterprise

IBM Big Data Hub

While many organizations have implemented AI, the need to keep a competitive edge and foster business growth demands new approaches: simultaneously evolving AI strategies, showcasing their value, enhancing risk postures and adopting new engineering capabilities. Otherwise, the risks become too significant.

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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. As copilot technology capabilities are changing rapidly, leaders should frequently identify metrics and evaluate strategies.

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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. The company must ensure that their sensitive information remains confidential and protected from potential competitors.

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Interview with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity

Corinium

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk. Now, there is a data risk here.

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The Royal Mint’s diversification means all change for IT and security

CIO Business Intelligence

Cybersecurity threats require business language lift This heightened business demand, along with the Royal moniker, does, however, come with risks. Three of the team—two cyber engineers and a risk manager—were hired directly from the University in their third years, prior to graduation. “We

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