New comment by throwawayjava in "Computer science as a lost art (2015)"

> What else are you going to do? Look at the stuff "deep" people are generally into, it mostly revolves around POSIX some way or another. And databases, but nobody wants to talk about that.

Self-driving cars (controls, perception, planning, safety, sensor design, localization, mapping, integration, security, etc.), human-competitive NLP/image classification, advanced robotics (repeat list from cars here but for things in the air, off-road, on the water, in the water, in orbit, in deep space, ...).

Those are all examples of real things that real people get to work on every day.

Operating systems topics don't even scrape the top 20 of stuff I think of when I think of deep expertise.

And even if we limit ourselves to the sort of things you mention, most people who work deeply on languages, tools, and standards view these as manifestations of their deep exploration rather than the focus or subject of the dive.

For example, TensorFlow. The framework very much is the product. But even if some other framework won the day tomorrow, the people who worked on TensorFlow would not have "wasted" their time thinking deeply about how to build the system.

This is why researchers whose original contributions were made in the 70s and 80s none-the-less continue to establish themselves as desired experts in new technology trends (e.g., Leslie Lamport and cloud computing or Martin Abadi and ML frameworks). Because they were focused on ideas and fundamental problems. The problems never disappeared, just changed form. And ideas have a lot more staying power than their manifestation in code.

Most people working deeply on systems today are not "revolving around POSIX in some way". See the proceedings of OSDI. And most deep experts choose other topics, most of which your post doesn't mention: graphics, programming languages (making them and analyzing programs written in them), compilers, security, robotics, user interfaces, NLP, ...

Your definition of "expert" seems to revolve around using things, mostly things based on ideas and techniques that were well-understood already 20 years ago and that are related to building a particular type of software system. Which, if anything, seems to deepen the author's point.

Someone gets to fill the AI research labs, staff the self-driving car companies, work at NASA, build core infra at large tech companies, and build the foundation for the next 20 years of trendy growth areas.

It's possible to get to those places without a degree, of course, but a degree is by far the path of least resistance. And in most of these cases, learning the material from the degree isn't optional; you're probably going to have hard time doing that controls engineering job at a self-driving car company if you never made your way through a calc sequence, some physics, and an algorithms course.

It's also worth noting that very often, building wordpress plugins pays more than doing all of those things I mentioned. I guess it's all about what you want to spend your life doing, which is exactly what the author says at the end of the article.

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