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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6 years ago
How to Hire a Data Scientist

 Now that artificial intelligence and machine learning have become increasingly common tools in a business’ arsenal, it is equally important to have employees who are capable of using – or developing – such tools. Chief among them should be a data scientist: someone with the experience and ability necessary to work with structured and unstructured data, and build systems capable of mining that data to come up with actionable and useful insights. The exact responsibilities of a data scientist can vary depending on the type of organization they work for,  which means that it’s up to an individual

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