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,...

Industry News

The Myth of the Mythical Unicorn

  Many have claimed recently that multifaceted data scientists are mythical beings, as impossible to find as unicorns. This itself is a myth, and a dangerous one at that. Hype is cyclic. A new idea excites people, exaggerated claims are made (and often believed), and the idea takes on bigger-than-life proportions. Eventually, however, reality sets

Making The Business Case For Predictive Talent Analytics

 A financial services powerhouse faced a 60 percent turnover rate among its 30,000 call-center reps. Leveraging predictive talent analytics, the organization reduced turnover by 30 percent and saved $5 million in the first year alone. A major...

Microsoft Adds Predictive Forecasting To Office 365

 Microsoft promised to bring analytics to a billion screens last February when it finally launched Power BI for Office 365. Starting this week, Office 365 users will be able to do both data mining and predictive forecasting....

Did Target Really Predict a Teen’s Pregnancy? The Inside Story

 We examine the origin and the facts behind this explosive story, the importance of headlines, and how unsubstantiated assumptions gain traction and mainstream attention and help create myths around Predictive Analytics. “How Target Figured Out A Teen...

It’s Already Time to Kill the “Data Scientist” Title

 What does it mean today to say your are—or want to be, or want to hire—a “data scientist?” Not much, unfortunately. The job title has almost as much ambiguity as the term “Big Data.” If you really...

As talent war intensifies, recruiters turn to analytics

 Baseball scouts used to scour the back roads of America in search of the next Mickey Mantle or Warren Spahn. Today, team front offices rely on reams of statistics and psychological profiles that help predict not only...

Q&A with Data and Analytics Expert Dean Abbott

 Data scientist Dean Abbott has been focusing on data mining and predictive analytics for more than 25 years, and has authored and co-authored several books including “Applied Predictive Analytics,” “IBM SPSS Modeler Cookbook” and contributed a biographical...

Big Data With a Personal Touch: The Convergence of Predictive Analytics and Positive Deviance

 Background Over the last few years, the triple aim has taken center stage in health care. Through more effective identification of individuals at higher risk, health care systems can become more strategic about resource allocation in order...

Social Security to step up fraud detection with predictive analytics

 Two major fraud incidents in the past year have spurred the Social Security Administration to step up its fraud detection and prevention efforts through the use of better analytics. The result is a  fraud prevention unit dedicated...

Top LinkedIn Groups in 2014 for Analytics, Big Data, Data Mining, and Data Science

 We analyze Top 30 LinkedIn Groups for Analytics, Big Data, Data Mining, and Data Science. Overall activity drops about 25%, but membership growth accelerates in Q4 2013. We identify 4 group quadrants and find which groups are...

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