The Enterprisers Project

enterprisersproject.com · Group blog · on HN since 2014

The Enterprisers Project is a Red Hat-sponsored site for IT leaders, covering open source adoption, CIO interviews and management.

What HN saysHN links it for explainers on topics like natural language processing, machine learning bias and hardware trends; commenters give no direct opinion of the site.
15HN people shared it
3linked it in comments
95stories submitted
155story points
6 months agolast shared
2014people per year2026

Most-shared posts

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    8 advantages of using open source in the enterprise
    2 people · 3 points · first shared 2015 · discussion on HN
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    Red Hat CEO on the death of version 2.0
    1 people · 8 points · first shared 2014 · discussion on HN
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    6 spooky tales from tech leaders on the workplace
    1 people · 4 points · first shared 2014 · discussion on HN
  8. 8
    DevOps is Not a Synonym for Application Development
    1 people · 4 points · first shared 2014 · 4 comments on HN
  9. 9
    5 TED talks every IT leader should watch
    1 people · 4 points · first shared 2015 · discussion on HN
  10. 10
    Why GE’s moving nearly 9,000 apps to the public cloud
    1 people · 4 points · first shared 2015 · discussion on HN
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    Gene Kim on how to get started with DevOps
    1 people · 3 points · first shared 2014 · discussion on HN
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    In IT, beware of fad versus functional
    1 people · 3 points · first shared 2014 · discussion on HN

What HN people wrote when they linked it

ghaff · 2020-09-20
It appears as if chipmakers will continue to drive things as small as they can, e.g. with EUV (finally). But the expectation is that a lot of continued performance gains will have to come through other means. These are some of the things that were talked about at the Hot Chips conference: https://enterprisersproject.com/article/2020/9/moores-law-what-means-t…
mtgx · 2016-09-23
It's important to keep in mind that in a "racist society" machine learning will also tend to be racist (but much more so). After all, the "AI" is learning from human data, so it's certainly not as objective as you would think a "machine" to be. https://www.propublica.org/article/machine-bias-risk-assessments-in-cr… https://enterprisersproject.com/article/2016/9/beware-biases-machine-l… http://www.nytimes.com/2016/06/23/us/backlash-in-wisconsin-against-usi…

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