3 ms·
Those of us doing it mostly roll our eyes at how VCs and (especially) marketers describe it, so I agree with you, but the "is it ML or stats?" conversation has
by 6gvONxR4sf7o 7y ago
Those of us doing it mostly roll our eyes at how VCs and (especially) marketers describe it, so I agree with you, but the "is it ML or stats?" conversation has been going nowhere for as long as this round of AI hype has been here.
That said, uber and lyft certainly benefit from much more interesting ML and stats than just "simple statistics." For example, setting prices and incentives to properly balance the driver side against the rider side of the marketplace.
- chubot 7y agoYeah I agree the argument is mostly about terminology. Anyway you slice it you have a bunch of data and you have a team that's improving the product with the data. That is for sure "table stakes". And yes I probably should have said "data science" or "statistics" rather than "simple statistics", definitely for Uber and Lyft (less so for smaller companies). I worked on a data science team 10 years ago when it was called "statistics". I even remember a 2009 NYTimes article that talked about data science without using the word "data science", because it hadn't come into use yet. If people want to redefine "machine learning" to mean "data science", OK fine. I guess that's what's happening now. The term "data science" already annoyed some people, but I guess now it's "machine learning" and "deep learning".