If you are hiring physicist to do Machine Learning, then you are doing it all wrong. Physicist are excellent at mathematical modeling, especially those in their 50s+. Data science from my experience is vastly inferior to mathematical modeling. The OP that wrote the article seems young, and doesn't seem like they've seen much. In the world of quantitative finance, physicists and mathematicians reign supreme. These guys get paid millions in salary and bonuses, because they earn 10x that for the firms. Their entire jobs are to mathematically model things. There are very successful hedge funds that only hire physicist and mathematicians. The current data science and machine learning is child's play compared to the stuff these quant funds do. Physicist, especially ones that have mathematical maturity are incredible assets, they have a lethal skillset that isn't really there in silicon valley. The majority of data science posts I see on HN are mediocre at best. I think age and experience are highly under valued. The physicists and mathematicians that Draper, Raytheon, DARPA, Renaissance Tech, Black Rock or Bridge Water (I would include SpaceX and Tesla in this list) have are superior to any data scientist that you will find in Silicon Valley. Mathematical modeling is incredibly hard, seasoned physicists are very good at it (I can't emphasize how difficult and long this process can be, nor can I articulate the reward for doing things this way).

> There is a definite sense of "physics is hard, therefore everything else must be easy" groupthink, combined with Dunning-Kruger syndrome.

You are severely misinformed, and you severely lack a breadth of industry experience. Physicists (especially the experienced ones)have something called mathematical maturity. Having mathematical maturity is a skillset, you are able to make precise formulations of some phenomenon you want to understand things about, and prove with rigor that your ideas are correct, or that they converge to what you want. This is a lethal mind to have, it's far superior to machine learning or data science. You aren't relying on heuristics like "overfitting". These concepts aren't well defined, and are very subjective.

I can tell you this with 100% confidence, AlphaGo, Duplex, Siri etc. are all gimmicks, no different from Watson or Deep Blue. They are just applying statistical brute force to narrow domains. I'd love to see a machine learning system that consistently matches the profits that the successful quantitative funds do. I know no tech company can do this, they don't have a fundamental understanding of mathematical analysis, they don't hire the right people. The right people are at DARPA, Draper, Tesla, SpaceX, any organization working on the hard sciences. Go figure; pretty much all of the major important discoveries came from either military or laborites investigating the hard science.

Data science/ML, is great for simple data sets (there is a mathematical definition of this, not heuristic). For many industrial problems like what SAP, or McKinsey does it's perfect. The available cloud compute power and a basic Statistics + CS degree will disrupt these businesses. But do know this: they are severely limited. Machine learning will very quickly start showing its cracks.