Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Hybrid AI Emerges To Tame LLMs – And Not A Moment Too Soon
 Originally published in Forbes The great potential of LLMs is...
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,...
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7 years ago
The Data Scientist: Specialist or Generalist

 By: Richard Boire, Senior Vice President, Environics Analytics For more from this writer, Richard Boire, see his session, “Demystifying Machine Learning-An Historical Perspective of What is New vs. Not New” at PAW Industry 4.0, June 19, 2019, in Las Vegas, part of Mega-PAW. As a practitioner with over 30 years of experience in the field, the discipline of data science has evolved dramatically. As I have discussed at length in previous articles and in my book, the approach and process in conducting data science exercises has not changed. Yet technology has transformed the discipline in that many tasks

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