ML and neural nets work surprisingly well on a lot of boring but important use cases. Optimizing online ad placement might be humdrum but it's the foundation of

ML and neural nets work surprisingly well on a lot of boring but important use cases. Optimizing online ad placement might be humdrum but it's the foundation of a $100B market in the US alone. [0] In my opinion the real hype is that ML has become so popular that new practitioners tend to forget other analytic techniques like SQL data warehouses. Interestingly these are starting to absorb ML capabilities like logistic regression, which are now accessible through SQL and can benefit from MPP and vectorwise query execute in DBMS types like ClickHouse, Vertica, and Google BigQuery. [1] https://www.forbes.com/sites/danafeldman/2018/03/28/u-s-tv-ad-spend-drops-as-digital-ad-spend-climbs-to-107b-in-2018/#31c701a77aa6 https://www.forbes.com/sites/danafeldman/2018/03/28/u-s-tv-a... Disclaimer: I work on ClickHouse.