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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6 years ago
Looking at Measurement and How We Evaluate the Impact of Reinforcement Learning Over Traditional Predictive Analytics

 Are we really at a new stage of so-called industrial development much like how the car replaced the horse and buggy as the main mode of consumer transportation? This would appear to be the case by some thought leaders and practitioner leaders that reinforcement learning (RL) will and should replace traditional prediction analytics as the mode of targeting. With my many years as a data science practitioner (30 years+), I have been trained in the discipline of measurement in evaluating what works vs. what does not work. In assessing the value of predictive models, the goal was to

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