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Lessons learned turning machine learning models into real products and services

O'Reilly Media - Data

Today, just 15% of enterprises are using machine learning, but double that number already have it on their roadmaps for the upcoming year. However, in talking with CEOs looking to implement machine learning in their organizations, there seems to be a common problem in moving machine learning from science to production.

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How Machine Learning is Used in Finance and Banking

Exadel

The banking landscape is constantly changing, and the application of machine learning in banking is arguably still in its early stages. Machine learning solutions are already rooted in the finance and banking industry. Machine learning solutions are already rooted in the finance and banking industry.

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10 top priorities for CIOs in 2025

CIO

Generative AI, when combined with predictive modeling and machine learning, can unlock higher-order value creation beyond productivity and efficiency, including accretive revenue and customer engagement, Collins says. The reality is that the transition is a long-term endeavor.

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What does an AI consultant actually do?

CIO

The spectrum is broad, ranging from process automation using machine learning models to setting up chatbots and performing complex analyses using deep learning methods. Working closely with IT, specialist and management teams. Project and change management. Ethical awareness and data protection.

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How Will Machine Learning and AI Change My Organization?

Dataiku

Whether businesses have a specific aversion to change or they simply find change too difficult to manage, the bottom line is that it holds companies back. Yet in the age of machine learning and AI, change is the new normal that the average enterprise will have to embrace.

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How today’s enterprise architect juggles strategy, tech and innovation

CIO

Strategic planning and demand/supply management is crucial to aligning resources with business goals and the enterprise architect has key input to this. Prioritization and planning: Enterprise architects must balance competing demands and prioritise initiatives that offer the most value.

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Building a vision for real-time artificial intelligence

CIO

Real-time AI brings together streaming data and machine learning algorithms to make fast and automated decisions; examples include recommendations, fraud detection, security monitoring, and chatbots. Real-time AI involves processing data for making decisions within a given time frame. It isn’t easy.