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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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6 years ago
Industrial Asset Optimization: Connecting Machines Directly with Data Scientists

 For more from this author, attend his virtual presentation, Industrial Asset Optimization:  Machine-to-Cloud/Edge Analytics, at Predictive Analytics World for Industry 4.0, May 31-June 4, 2020.  For industrial firms to realize the benefits promised by embracing Industry 4.0, the access to clean, quality asset data must improve.  Most of a data , scientist’s work, in any vertical, involves cleaning and contextualizing data, or “data prep”.  In the industrial segment, this remains true, and, considerably more challenging. Enterprise-wide data ingest platforms tend to yield inefficient, incomplete data necessary to optimize assets at the application layer.  In order to improve this,

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