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Automating Model Risk Compliance: Model Validation

DataRobot Blog

What are some steps that the modeler/validator must take to evaluate the model and ensure that it is a strong fit for its design objectives? Evaluating ML models for their conceptual soundness requires the validator to assess the quality of the model design and ensure it is fit for its business objective.

Risk 52
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Building cyber resiliency for your data with IBM FlashSystem

IBM Big Data Hub

To combat these ever-growing risks, the concept of cyber resiliency has gained significant importance. In this blog, we will explore the concept of cyber resiliency from an IBM® perspective and how our approach can help organizations protect themselves in an ever-changing cybersecurity landscape.

Risk 78
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Enterprises’ best bet for the future: Securing generative AI  

IBM Big Data Hub

More than 50% of respondents are concerned about unpredictable risks impacting generative AI initiatives and fear they will create increased potential for business disruption. AI that strays from what it was operationally designed to do can introduce new risks with unforeseen business impacts.

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How to build a successful procurement strategy

IBM Big Data Hub

By assessing and proactively managing risks inherent in the supply chain , organizations can shield themselves from disruptions and strengthen the resilience of their operations. This enables an effective and adaptive approach to sourcing that creates value and minimizes risk.

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Business Strategies for Deploying Disruptive Tech: Generative AI and ChatGPT

Rocket-Powered Data Science

First, don’t do something just because everyone else is doing it – there needs to be a valid business reason for your organization to be doing it, at the very least because you will need to explain it objectively to your stakeholders (employees, investors, clients).

Strategy 290
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AI search and RAG at Microsoft Build 2024 – what does this mean for businesses?

Jen Stirrup

In this blog post about Microsoft Build 2024, I will focus on AI Search and RAG modelling. In content generation, RAG models can produce high-quality, relevant content using up-to-date external sources to support different objectives, such as marketing and communication. What are the risks of RAG for businesses?

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Balancing AI: Do good and avoid harm

IBM Big Data Hub

” Read the “Presidio AI Framework” paper to learn how to address generative AI risks with guardrails across the expanded AI life cycle As generative AI continues to go mainstream, organizations are excited about the potential to transform processes, reduce costs and increase business value.