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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8 years ago
Data Reliability and Validity, Redux: Do Your CIO and Data Curators Really Understand the Concepts?

 Here are two recent entries on the big but neglected issue of data reliability and analytic validity (DR&AV), from the vast commentariat that is LinkedIn: One of my complaints with hashtag#bigdata, is there isn’t enough focus on getting the right kind of data. We deal with this in healthcare all the time. Much of our transactional data is just outcomes. There’s a push in the industry to change health behaviors (generally: population health). But if we’re not collecting meaningful behavioral data (could be secondary data like credit card purchases or primary like surveys about health attitudes), we can’t

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