Machine Learning Times
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AGI Is Infeasible. Instead, Pursue Superhuman Adaptable Intelligence
  Originally published in Forbes On a recent episode of the...
Artifact-Driven Development: Making It Possible to Query Large Analytics and AI Projects
 A practical introduction to making complex project structure explicit...
Incoherent AGI Hype Spurs An Industrywide Pivot To Hybrid AI
  Originally published in Forbes Recently on The Dr. Data Show,...
The AI Paradox: More Humanlike Means Less Autonomous
  Originally published in Forbes The AI executives are at...
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10 years ago
Breaking into Analytics: 5 “Musts” for your Career Transition

 In our data-rich society, corporations of all types and sizes recognize the importance of utilizing information to understand their past and shape their future. Many organizations, however, ultimately fail to reap the powerful benefits of analytics as a business tool because, they believe, their analysts have failed to deliver valuable, pertinent insights from the data that can drive business-critical strategies and success. The analytics project that once seemed so promising is forgotten. Was it management’s inattention? Lack of budget? Faulty data or a flawed hypothesis? Or were the analysts on the project not really analysts at all? Analytics

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