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ML is not magic. If you can't run controlled experiments then it isn't actually very easy to make confident recommendations about improvements to business processes.


Sure, I was exaggerating for effect. Maybe not proper ML, but something more like the OS automatically generating (and discarding if unused) macros in the background, and using CV / OCR on the windows to try to interpret what the user is doing - I am sure v1.0 would be laughable, but eventually...


can you give some examples? i don't think the average medium sized business has many obvious use cases for ML.

this article by evan miller does a good job of explaining why: https://www.evanmiller.org/predictive-analytics.html


someone working for palantir in a business development role did some business development. why is this a news story?


that is what they claim they are able to do. the reality is likely quite different.


Cambridge Analytica didn't conduct marketing for Brexit campaign groups.


Cambridge Analytica didn't conduct marketing campaigns for Brexit.


comparing aggregate rates of household formation vs housebuilding doesn't tell you very much as household formation is dependent on housing supply.

in the absence of supply constraints, if the price goes up this creates an incentive to build more houses, which will balance out any increased demand. there is also good research that shows supply constraints do matter in the UK - http://personal.lse.ac.uk/hilber/hilber_wp/Hilber_Vermeulen_...


it's hard to understand how this actually gets used for those of us not in enterprise IT. would be great to see an example of a real project using Mule (or similar products).


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