June 29th, 2017
(written by lawrence krubner, however indented passages are often quotes). You can contact lawrence at: firstname.lastname@example.org
Now consider my most viral tweet so far:
Good CS expert says: Most firms that think they want advanced AI/ML really just need linear regression on cleaned-up data.
This got almost universal agreement from those who see such issues play out behind the scenes. And by analogy with the pipe innovation case, this fact tells us something about the potential near-term economic impact of recent innovations in Machine Learning. Let me explain.
Most firms have piles of data they aren’t doing much with, and far more data that they could collect at a modest cost. Sometimes they use some of this data to predict a few things of interest. Sometimes this creates substantial business value. Most of this value is achieved, as usual, in the simplest applications, where simple prediction methods are applied to simple small datasets. And the total value achieved is only a small fraction of the world economy, at least as measured by income received by workers and firms who specialize in predicting from data.