Not a software engineer, but a student in the process of becoming one. I personally feel that the goal of university / school is not necessarily too get a lot of essential daily-use skills that will be used in the job, but more as a training for the brain. When I got my first internship, I noticed that I barely used any of the skills learned in university except a couple, but my ability to adapt to a new environment and new codebase had increased tenfold in comparison to previous years.
I may very well be wrong and have no job waiting for me in a couple years, but I feel like the goal of university should be to train the brain and become accustomed to software. The world of software is too large to be able to successfully teach the entirety of it in a couple years, so the next best thing is to prepare the students so they optimize any future learning.
For AI usage in class, I would do the same as in my university. The projects you can do as you like, but the exams are on paper and without AI. So if you choose to use AI for your projects, get ready for the exam because you may struggle there.
A subject that I feel is practically useless is for example Theory of Computation, but it has been one of my favorite subjects because it has forced me to think in some ways that I didn't before, and I have learnt a lot from it.
Was just about to say the same thing. It is kind of scary how the only way to pin accountability onto a human/ agent is by making it fear some sort of consequences. Make a mistake - get fired and lose your source of income. But of course, applying the same logic to an agent seems like a fast track to a redo of Terminator, but in real life.
I can see that in practice the bottleneck isn't the automata construction, I'm just curious of how the construction is approached with such a super-exponential conversion algorithm
Quick question:
Isn't the construction of a NFA - DFA a O(2^n) algorithm? If a JSON file has a couple hundred values, its equivalent NFA will have a similar amount, and the DFA will have 2^100 states, so I must be missing something.
I may very well be wrong and have no job waiting for me in a couple years, but I feel like the goal of university should be to train the brain and become accustomed to software. The world of software is too large to be able to successfully teach the entirety of it in a couple years, so the next best thing is to prepare the students so they optimize any future learning.
For AI usage in class, I would do the same as in my university. The projects you can do as you like, but the exams are on paper and without AI. So if you choose to use AI for your projects, get ready for the exam because you may struggle there.
A subject that I feel is practically useless is for example Theory of Computation, but it has been one of my favorite subjects because it has forced me to think in some ways that I didn't before, and I have learnt a lot from it.