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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11 years ago
The Imminent Future of Predictive Modeling

 Predictive modeling tools and services are undergoing an inevitable step-change which will free data scientists to focus on applications and insight, and result in more powerful and robust models than ever before. Amongst the key enabling technologies are new hugely scalable cross-validation frameworks, and meta-learning. Over the past two to three years there has been a small explosion of companies offering cloud-based Machine Learning as a Service (MLaaS) and Predictive Analytics as a Service (PAaaS). IBM and Microsoft both have major freemium offerings in the form of Watson Analytics and Azure Machine Learning respectively, with companies like BigML,

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