Machine Learning Times
EXCLUSIVE HIGHLIGHTS
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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Uncle Sam Wants Your Deep Neural Networks

   Originally published in NYTimes, June 22, 2017 SAN FRANCISCO — The Department of Homeland Security is turning to data scientists to improve screening techniques at airports. On Thursday, the department, working with Google, introduced a $1.5 million contest to build computer algorithms that can automatically identify concealed items in images captured by checkpoint body scanners. The government is putting