My view is: (1) Software is well on the way to an old, slowly changing, mostly routine, boring, low margin, slow growth business and industry. (2) That the ge

My view is: (1) Software is well on the way to an old, slowly changing, mostly routine, boring, low margin, slow growth business and industry. (2) That the general purpose computing hard/software and 100 Mbps Internet data rates are all so cheap will in places undercut large, expensive approaches to computing projects. E.g., people will do projects, but Sand Hill Road need not be more involved than they are now in, say, a new pizza shop in Peoria, not more involved than they were in the romantic matchmaking Web site Plenty of Fish. (3) A huge problem for computing causing (1) is that there just are not enough good, new ideas for high value IT startups. For a joke, but a simple explanation, the days of a hot social, mobile, local sharing app are gone. (4) For Evans's dreams about machine learning (ML), he is not very well informed and is not seeing very clearly, but in principle, if strain to extend the meaning of ML, he is correct about the potential. But in practice that future will come slowly, very slowly. Why so slowly? In fact, e.g., looking at, say, scikit, that's basically some applied math, and nearly all the math there is now old enough to have long, gray whiskers, literally. That applied math and much more in optimization, simulation, experimental design and analysis of variance, stochastic processes, on and on, i.e., the math sciences, optimization, operations research, statistics, except for a few niches (e.g., optimization in operating oil refineries, the fast Fourier transform for oil prospecting, partial differential equations for modeling oil reservoirs, air line crew scheduling, maybe airline plane scheduling, statistics in biomedical research and development) hasn't caught on at all well generally in business; so there is only tiny reason to believe it will become "The next big thing" now. For that math, it's not so easy to get good at it: (A) The pure math departments don't want to teach it. (B) Very few other departments have enough grounding in the math prerequisites to teach the material very well. (C) Except for a few niches, business has long made its position crystal clear -- such applied math and a dime won't cover a 10 cent cup of coffee. (D) It has long been the case and still is that about the only paying customer that takes such applied math seriously is the US DoD for purposes of US national security. Run a good applied math project down Sand Hill Road, for a big problem, with running prototype software, and will hear laughs, silence, or "don't call us; we'll call you". I have to doubt if there is a single information technology (biotechnology can be different) VC firm on Sand Hill Road able to direct technical due diligence for an applied math project. There can't be "The next big thing" without a few hundred times more well qualified startup founder, worker bee, applied mathematicians to do the work.