Academia was not initially tasked with the purpose of preparing students for careers in industry. Academic interests are purely that: academic. They serve no intended purpose necessarily beyond their contribution to knowledge, understanding, and often the enjoyment of academics. In some cases, there is overlap between concepts of interest to academics and those in industry. However, to expect an undergraduate degree in an academic discipline, such as computer science, to prepare you for the needs of modern industry is to confuse the priorities and values of academia and industry. You can raise the question of, 'should this be the case?' and of course the answer will vary across fields, academics within fields, and students too. However, I would suggest that it may be an error to value the profit-driven needs of the industrial world to those of the academic world, which veer closer to having a value derived from the intrinsic nature of knowledge itself. If you want a school to teach you how to solve problems for Google or Facebook, I don't believe such a school should come at the cost of replacing the function and values of academia itself; perhaps some fields/departments in academia should extend study and degrees in the direction of industry-motivated study or new schools should open with such a focus. But don't be confused with your expectations that academic study should provide any tangible value in a capitalistic world.
This is a good comment, but I suggest you make some paragraphs! It's a bit hard to parse atm.
To add on to what you said, many academics pursue knowledge for its own sake. In many cases, especially in theory, the value of new knowledge may not be known at the time of its discovery.
For example, the multi armed bandit problem was formalized by Herbert Robbins in the 50s. It was almost universal declared a negative result. Now, bandit algorithms are classified as some of the most commercially succesful applications of machine learning algorithms (ad placement, recommendation, experimental design), and the corresponding techniques used in the formal analysis of bandit algorithms are widely used in 'non-bandit' settings (see ICML's test of time award this year).
It always saddens me to see negative comments about academics & ignorance about 'the point' of academia.
Automata allow us to rigorously argue about computation based on the simplest machines we can conceive of. If you can not make strong claims about automata, then you have no chance of making strong claims on "real world" (whatever that is) machines.
