Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Survey: Machine Learning Projects Still Routinely Fail to Deploy
 Originally published in KDnuggets. Eric Siegel highlights the chronic...
Three Best Practices for Unilever’s Global Analytics Initiatives
    This article from Morgan Vawter, Global Vice...
Getting Machine Learning Projects from Idea to Execution
 Originally published in Harvard Business Review Machine learning might...
Eric Siegel on Bloomberg Businessweek
  Listen to Eric Siegel, former Columbia University Professor,...

Machine Learning

Why AI Isn’t Going to Replace Data Scientists Any Time Soon

 Should data scientists consider AI a threat to their short- or even long-term job security? In this article, I present a philosophical argument that adamantly argues, “No.” For the work of data scientists, and human endeavors in general, machines are nowhere near human intellectual capabilities. There has been much discussion, almost euphoric in some instances,

How Machine Learning Gave Australia An Edge in the Tokyo Pool

 Originally published in The Sydney Morning Herald, Aug 12, 2021. When Cate Campbell touched the wall ahead of American Abbey Weitzeil in the final leg of the women’s medley relay in Tokyo, it signified the end of...

Twitter AI Bias Contest Shows Beauty Filters Hoodwink the Algorithm

 Originally published in CNET.com, Aug 9, 2021. The service’s algorithm for cropping photos favors people with slimmer, younger faces and lighter skin. A researcher at Switzerland’s EPFL technical university won a $3,500 prize for determining that a...

Training Self-Driving Cars for $1 An Hour

 Originally published in RestoftheWorld.org, Aug 3, 2021. To master the roads, autonomous vehicles need lots of data. Workers everywhere from Kenya to Venezuela are providing it. Every day for over four years, Ramses woke up in his...

Researchers: Instagram ‘Bullied’ Us Into Halting Algorithmic Research

 Originally published in Gizmodo, Aug 13, 2021. For the second week in a row, Facebook killed a project meant to shed light on its practices. A Berlin-based nonprofit studying the ways in which Instagram’s algorithm presents content...

“Doing AI” Is a Mistake that Detracts from Real Problem-Solving

  A note from Executive Editor Eric Siegel: Richard Heimann’s forthcoming book, Doing AI, takes on the problems with “AI” as a brand with a style so crisp, clear, and unique, it just pops off the page....

Getting the Green Light for a Machine Learning Project

  This article is based on the transcript of one of 142 videos in Eric Siegel’s online course, Machine Learning Leadership and Practice – End-to-End Mastery. Originally published by SAS Blogs How do you internally sell a...

How AI Will Help Keep Time at the Tokyo Olympics

 Originally published in Wired, July 24, 2021. Omega, the official timekeeper of the Games, is now using computer vision and motion sensors for events like swimming, gymnastics, and beach volleyball. Timing of Olympic races has not always...

Why Schools Need to Abandon Facial Recognition, Not Double Down On It

 Originally published in Fast Company, July 23, 2021. With the loosening of COVID-19 restrictions and the end of summer quickly approaching, schools are preparing to welcome students back into their classrooms for in-person learning. With that transition...

Elon Musk Just Now Realizing That Self-Driving Cars are a ‘Hard Problem’

 Originally published in The Verge, July 5, 2021: Tesla CEO Elon Musk is finally admitting that he underestimated how difficult it is to develop a safe and reliable self-driving car. To which the entire engineering community rose...

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