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
The Art of Data Science

 With much of the latest discussion focused on the latest techniques in machine learning  and in particular deep learning, the significant benefits of machine learning and deep learning are now a public reality. Yet, machine learning in effect represents the predictive analytics techniques that have been used for many years by data scientists.  Furthermore, data scientists and their end users have always recognized the huge economic advantages of predictive analytics. But the significant advances of deep learning in the last 5 years have just expanded the application of predictive analytics to other areas which were technically not feasible

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