
80% of all machine learning engineers work at Google or Facebook - thetall0ne
https://medium.com/@aaronedell/80-of-all-machine-learning-engineers-work-at-google-or-facebook-6a8e315436e8
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minimaxir
You can't promote your own tool at the top of a unbiased-list-of-good-tools
without disclosure. (EDIT: I see it was added)

Also the blog/submission title is clickbait and likely an outright lie. From
the original article/thoughtpiece
([https://www.forbes.com/sites/groupthink/2018/02/09/tradition...](https://www.forbes.com/sites/groupthink/2018/02/09/traditional-
recruiting-isnt-enough-how-ai-is-changing-the-rules-in-the-human-capital-
market/#4b281e0c274a)) you cite as a source, emphasis mine.

> For example, fully 80 percent of machine learning engineers _with Ph.D.s_.
> are scooped up by Google and Facebook, especially those that have patents.

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jasonmaydie
How would you build a business on something you do not understand well? I've
worked with startups who could not get past that 80% barrier you run into with
your machine learning algorithms. They didn't know if their data was bad,
their algorithm was bad or whatever the issue was because they ere not using
data a human could easily conceptualize.

~~~
Eridrus
One of the more surprising things about ML is that it can look like it's
working, even when there are horrible bugs.

This makes testing even more important than usual, but testing ML systems is
even harder than testing normal software, so you're in a shitty place either
way.

ML ends up being this sort of bimodal level of difficulty, either it's super
easy and everything works without much effort (it happens sometimes), or it
doesn't work quite how well you need it to and you should probably be ready to
sinks many months into it.

