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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8 years ago
Are We Using Machine Learning?

 In the midst of a recent engagement an executive suddenly asked, “Are we using Machine Learning?”.  This caught us off-guard; working in the field for many years, we use the “learning sciences” virtually every day to solve hard problems.  Machine Learning (ML), Data Science (DS) and Artificial Intelligence (AI) are exciting and very powerful; still, we’re happy to use conventional techniques whenever they’re the best choice to solve the client’s challenge.  But I can understand where the question came from, given the hype surrounding ML, DS, and AI. (Sometimes, interest in inner details exceeds interest in more important

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