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The Role of Model Governance in Machine Learning and Artificial Intelligence

Domino Data Lab

In the world of machine learning (ML) and artificial intelligence (AI), governance is a lifelong pursuit. All models require testing and auditing throughout their deployment and, because models are continually learning, there is always an element of risk that they will drift from their original standards.

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Application Development Consulting Helps Companies Get the Most of AI

Smart Data Collective

Many of them have utilized many management programs but finding the most best application without the assistance of an experienced consultant can be a challenge. Some new consulting agencies specialize in helping companies select the best applications. Application development consulting services are a newer service.

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Global AI regulations: Beyond the U.S. and Europe

CIO Business Intelligence

Importantly, where the EU AI Act identifies different risk levels, the PRC AI Law identifies eight specific scenarios and industries where a higher level of risk management is required for “critical AI.” Babin has extensive experience as a senior management consultant at two global consulting firms.

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AI and cybersecurity: A double-edged sword

CIO Business Intelligence

By leveraging machine learning algorithms, AI can analyze user behavior and network traffic patterns, identifying anomalies that might indicate insider threats or other malicious activities. Perhaps one of the most anticipated applications of AI in cybersecurity is in the realm of behavioral analytics and predictive analysis.

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Why HR professionals struggle with big data

CIO Business Intelligence

By collecting and evaluating large amounts of data, HR managers can make better personnel decisions faster that are not (only) based on intuition and experience. This makes it impossible to identify any correlations, explains Viole Kastrati, Senior Consultant SAP BI & Analytics at Nagarro.

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The new calling of CIOs: Be the moral arbiter of change

CIO Business Intelligence

Consulting giant Deloitte says 70% of business leaders have moved 30% or fewer of their experiments into production. We use machine learning all the time. These issues mean many gen AI projects remain stuck at the prototyping stage. Currently, we don’t have gen AI-driven products and services,” he says. “We

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AI on the mainframe? IBM may be onto something

CIO Business Intelligence

Rather than pull away from big iron in the AI era, Big Blue is leaning into it, with plans in 2025 to release its next-generation Z mainframe , with a Telum II processor and Spyre AI Accelerator Card, positioned to run large language models (LLMs) and machine learning models for fraud detection and other use cases.