Remove Experimentation Remove Modeling Remove Reporting Remove Risk Management
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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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3 key digital transformation priorities for 2024

CIO Business Intelligence

The analyst reports tell CIOs that generative AI should occupy the top slot on their digital transformation priorities in the coming year. Moreover, the CEOs and boards that CIOs report to don’t want to be left behind by generative AI, and many employees want to experiment with the latest generative AI capabilities in their workflows.

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7 steps for turning shadow IT into a competitive edge

CIO Business Intelligence

There are ample reasons why 77% of IT professionals are concerned about shadow IT, according to a report from Entrust. Set parameters and emphasize collaboration To address one root cause of shadow IT, CIOs must also establish a governance and delivery model for evaluating, procuring, and implementing department technology solutions.

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AI Governance: Break open the black box

IBM Big Data Hub

It is well known that Artificial Intelligence (AI) has progressed, moving past the era of experimentation. Today, AI presents an enormous opportunity to turn data into insights and actions, to amplify human capabilities, decrease risk and increase ROI by achieving break through innovations. Challenges around managing risk.

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Five open-source AI tools to know

IBM Big Data Hub

When AI algorithms, pre-trained models, and data sets are available for public use and experimentation, creative AI applications emerge as a community of volunteer enthusiasts builds upon existing work and accelerates the development of practical AI solutions.

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Bring light to the black box

IBM Big Data Hub

It is well known that Artificial Intelligence (AI) has progressed, moving past the era of experimentation to become business critical for many organizations. Success in delivering scalable enterprise AI necessitates the use of tools and processes that are specifically made for building, deploying, monitoring and retraining AI models.

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20 issues shaping generative AI strategies today

CIO Business Intelligence

Just look at the stats:Some 45% of 2,500 executives polled for a May 2023 report from research firm Gartner said the publicity around ChatGPT prompted them to increase their AI investments, 70% said their organization is already exploring gen AI, and 19% are in actual pilot or production mode. How has, say, ChatGPT hit your business model?”