We have to separate three things. First - there is much more data now than 5 or 10 years ago; it is generated by every process and is easy to store. Second -

We have to separate three things. First - there is much more data now than 5 or 10 years ago; it is generated by every process and is easy to store. Second - there is a greater art and capability to aggregate and manipulate data. It's simply faster, but also there is a lot of supporting technology in the form of workflows and tooling. Third - there are more algorithms now; these are often derived from AI research (DNN, RNN, Bayesian things..) The first two definitely mean that linear regression can generate much more value than 10 years ago. The third one is a product of the frustration with linear regression and many other "traditional" algorithms. In many domains (speech, images, text processing) the community smashed its head on the wall for 30 years before the computational resources and algorithmic tricks that came out in 2010->now came on stream. You just can't do much with TFIDF or similar with text - I tried very very hard; on the other hand using a transformer is like bloody magic.