Machine Learning Times
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Hybrid AI: Industry Event Signals Emerging Hot Trend
 Originally published in Forbes After decades chairing and keynoting myriad...
Predictive AI Thrives, Despite GenAI Stealing The Spotlight
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For Managing Business Uncertainty, Predictive AI Eclipses GenAI
  Originally published in Forbes The future is the ultimate...
AI Business Value Is Not an Oxymoron: How Predictive AI Delivers Real ROI for Enterprises
  Originally published in AI Realized Now “Shouldn’t a great...
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Eric Siegel, scholar, consultant and event organizer, explains how, where and why predictive analytics can be used to inform more proactive, empirically-based decision making. As part of his time at Cognizant Confluence 2011, Siegel brings a lot of good points to the table here, offering insights into why predictive analytics are useful and which business practices they can be most helpful to. The idea of predictive analytics is pulled from a lot of unstructured data, AKA Big Data. It is this unstructured data that offers valuable information and learning opportunities. And as Siegel says, “There’s never enough data” when it comes to analytics.

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