> developing an organisational capability to design, build, and deploy successful machine learned models in user-facing contexts is, in my opinion, as fundamental to an organisation’s competitiveness
You hear that, right? In 2019 already you have to have AI and do it well to be competitive. I just wanted to point out how cyberpunk that is.
>... I just wanted to point out how cyberpunk that is.
Nah, that is corporate flavor of the month/year/etc. It's not the 90s, so they're not "synergizing" any more but otherwise, whatever.
In #devops is turtle all way down but at bottom is perl script. - @devops_borat
Comedy: You, trying to launch a startup from scratch using Java. Tragedy: Me, trying to debug 27k lines of legacy Perl that brings $113MM/yr - @NeckbeardHacker
Today's ML is really good at speech and image recogniziton, which makes for some very eye-popping layman demos.
Whereas what businesses really want is time series prediction, and modern ML really sucks balls at solving this problem.
I agree on the former, and quite strongly disagree on the latter, even if it means redefining ML to be dressed-up statistics.