If you mean acquiring facts, maybe not. If you mean getting better at a skill such as programming or playing the piano, how could you possibly get better without challenging yourself?
It's rational for most candidates to study interview prep books because that is what the majority of companies want. Not saying I like it, but why would you want to filter out candidates who are just using basic common sense?
Of course it's not strictly necessary to learn the various levels of abstractions in computing. But some people just do it out of curiosity and wanting to know how things work from the ground up. These people typically tend to be smarter and better, but it's true that not everyone needs to do this to have a good career and make lots of money.
An AI being able to create arbitrary computer programs and work productively in an arbitrary codebase sounds basically like an AGI or something approximating it. Not sure if that's what you're implying is a few years away. I do think it's inevitable, but the time horizon still doesn't seem clear to me at all
Thanks for the informative comment. Are there resources you would recommend for learning more about performant algorithms? At the moment I'm just messing around with JUCE
It's a primary source of information for over a billion people at this point. It's probably not a good idea to have that monopolized by corporate or government interest
Are engineers creative? Physicists? Mathematicians? I don't know if you have a very narrow definition of creativity or if you seriously think that the people who created all the software that you use everyday are not creative
These toy projects are worth doing if you want to continuously build your skills and like knowing how things work at a fundamental level. If you want to create an OS, it will obviously never be used by anyone ever and in that sense it's "useless", but you learn a lot in the process and it's fun.
This is basically meaningless if you don't qualify why you think so. He is a harvard medical doctor and one of the leading researchers in the field, so I'd like to know what makes him a fraud
A bit off topic but how much of data science work requires this probability/statistics knowledge on the job? I've heard you basically need a PhD to do modelling and "real" data science