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Professor solves 240 computer science exam problems in 4 hours [video]

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Re: Professor solves 240 computer science exam problems in 4 hours [video]

#41
post #37

Watched a bit as I never came across these terms.. Staring at the wikipedia page of "Regular language" and I still dont get what is the purpose of this. Anyone, not in academia preferably, using this for practical applications? What ARE the practical applications?

I don't think there are a lot of direct practical applications, outside of regular expressions for string search as others have mentioned. This is a building block to more advanced topics, some of which have practical applications. Theory of designing programming languages, and computational complexity theory. For instance, these are like baby steps toward P vs NP.

Re: Professor solves 240 computer science exam problems in 4 hours [video]

#42
post #41
post #37

Watched a bit as I never came across these terms.. Staring at the wikipedia page of "Regular language" and I still dont get what is the purpose of this. Anyone, not in academia preferably, using this for practical applications? What ARE the practical applications?

I don't think there are a lot of direct practical applications, outside of regular expressions for string search as others have mentioned. This is a building block to more advanced topics, some of which have practical applications. Theory of designing programming languages, and computational complexity theory. For instance, these are like baby steps toward P vs NP.

Another reason this subject is taught, besides the topics themselves, is that it develops your logical reasoning, abstraction, and visualization muscles. For example the first problem, he has to argue that L concatenated with L-reversed is regular, and he uses general properties of regular languages to do it. Then to argue the prefix and suffix parts, he has to utilize the automaton for L by making copies of it and drawing transitions between them. A final example is the famous and dreaded "pumping lemma" that gives practice understanding alternating quantifiers: there exists a such that for all b, ....

Re: Professor solves 240 computer science exam problems in 4 hours [video]

#43
I need to defend theory of computer science here, it seems. Please note that this computer science, not computer engineering. The idea of automata, regular languages, turing machines, and whatnot inform some of the most fundamental results of computer science.

At least in the fields where I work [compilers, formal verification], all of the above theory is common parlance. Everyone working on this stuff knows all of the above theory, since it forms the bedrock of a large part of what we do and how we think about the world. Knowing the complexity of the algorithms we use, the languages we parse, issues of decidability, etc. all crop up. That's because it's science, not engineering. GATE is meant as an entrance exam to pursue a graduate degree in computer science.

The fact that one does not need this during their day job is, dare I say it, irrelevant. This feels to me like people complaining that number theory is completely useless in the 19th century; Indeed it was... until it wasn't, and we needed cryptography.

This stuff is useful right now in a 'how to think about the world' kind of way. Knowing the power differences between automata, transducers, push down automata, and turing machines is critical in disparate applications involving formal verification. The difference in power of these different representations impacts what we can "do" with them. The knowledge of this hierarchy fundamentally shapes how I view the world.

Re: Professor solves 240 computer science exam problems in 4 hours [video]

#44
post #21
post #18

Earlier quoted context omitted.

Probably a true statement for every theoretical academic field. Yet, very mysteriously the obscure academic problems have produced our great wealth of technology. I find this fascinating.

Except they haven't, mostly internalized (sometimes stolen) and formalized achievements of free risk takers, who don't bother writing textbooks.

How did we get the atom bomb and the internet?

Re: Professor solves 240 computer science exam problems in 4 hours [video]

#45
post #44
post #21

Earlier quoted context omitted.

Except they haven't, mostly internalized (sometimes stolen) and formalized achievements of free risk takers, who don't bother writing textbooks.

How did we get the atom bomb and the internet?

Internet story is mostly a fairytale, specifically modern stupidity of "fathers" shows this. They were just riding on the wave of something that everyone were experimenting with at that time.

A-bomb was about pulling some people away from academia, not building it by academia.

"Built by academia" result is something we can see with colliders.

Re: Professor solves 240 computer science exam problems in 4 hours [video]

#46
post #43

I need to defend theory of computer science here, it seems. Please note that this computer science , not computer engineering . The idea of automata, regular languages, turing machines, and whatnot inform some of the most fundamental results of computer science . At least in the fields where I work [compilers, formal verification], all of the above theory is common parlance. Everyone working on this stuff knows all o…

Some people are more inclined to theoretical concepts, some people are more practical. Both have an understanding on how things work and/or an intuition, either by studying theoretical concepts or via practical, hands on experience.

My issue with this, and this is mostly my own personal opinion, is not whether or not this subject is important and that we need to defend it, but whether teaching it to students of that level is the 'right' thing.

Imagine a student that doesnt even know how to program yet, doesn't know any algorithms, or higher level paradigms, heck doesnt even know any computer architecture stuff yet, but has to go through this block of theory and get examined on it.. Is it the right move to motivate more people into this field?

Re: Professor solves 240 computer science exam problems in 4 hours [video]

#47
post #13

Skimming through the pages on the video, it shows vividly how far away academia is from real life problems.

I guess this is a bit like the Someone Else's Problem phenomenon. Nobody needs to know about compilers, operating systems or analysis of algorithms because Somebody Else will deal with those things.

[deleted]

Re: Professor solves 240 computer science exam problems in 4 hours [video]

#48
post #46
post #43

I need to defend theory of computer science here, it seems. Please note that this computer science , not computer engineering . The idea of automata, regular languages, turing machines, and whatnot inform some of the most fundamental results of computer science . At least in the fields where I work [compilers, formal verification], all of the above theory is common parlance. Everyone working on this stuff knows all o…

Some people are more inclined to theoretical concepts, some people are more practical. Both have an understanding on how things work and/or an intuition, either by studying theoretical concepts or via practical, hands on experience. My issue with this, and this is mostly my own personal opinion, is not whether or not this subject is important and that we need to defend it, but whether teaching it to students of that…

> My issue with this, and this is mostly my own personal opinion, is not whether or not this subject is important and that we need to defend it, but whether teaching it to students of that level is the 'right' thing.

Teaching it to which students? If someone enrolls in a computer science class, it's reasonable to teach them computer science. If instead they want a mechanical introduction to programming, CS probably isn't the right material.

Re: Professor solves 240 computer science exam problems in 4 hours [video]

#49
post #44
post #21

Earlier quoted context omitted.

Except they haven't, mostly internalized (sometimes stolen) and formalized achievements of free risk takers, who don't bother writing textbooks.

How did we get the atom bomb and the internet?

The perception of people in academia is that innovation is the product of knowledge. That may have been true in the US. It has been true pretty much nowhere else (not for anything else, the real world is rarely so kind as to present solutions on a plate).

Korea, to name the best example, takes education extremely seriously...and they have had severe difficulty turning that into innovation (outside the chaebols, there is basically no R&D occurring).

I would also look at the exam being tested here. This is India, a system that is notoriously reliant on rote memorisation and turning out employees who crumble under pressure and cannot operate without very specific instructions. Again, this is not a coincidence.

The source of innovation isn't knowledge by the coincidence of knowledge, creativity, and opportunity. Knowing something is quite different from being able to understand and use it. Stuff like the atom bomb are entrepreneurial triumphs by people who happened to be academics.

(The university I attended pioneered AI in the 60s, they had the DoD battering down their door...they refused every opportunity, and doubled down in the ivory tower. Result? No serious innovation since the 60s, and most PHd students going elsewhere to do "real work". This kind of thing just doesn't happen in the US but is the most common result outside of the US.)

Re: Professor solves 240 computer science exam problems in 4 hours [video]

#50
post #43

I need to defend theory of computer science here, it seems. Please note that this computer science , not computer engineering . The idea of automata, regular languages, turing machines, and whatnot inform some of the most fundamental results of computer science . At least in the fields where I work [compilers, formal verification], all of the above theory is common parlance. Everyone working on this stuff knows all o…

A lot of people give theory a lot of crap. But that's normally because they are not comfortable with the material.

If you are comfortable with the material, you see applications for it all over the place, and use it all the time. Sure, you don't have to ground your system in some kind of formal model (you can just code-til-it-works), but when you do I've found it always ends up as a far simpler and more resilient product.

It's kind of like people who complain that math is useless in school and you'll never need it. Sure, if you never really master it, you'll never be able to use it, so you'll make things kinda work in ways that don't strictly require it, and then conclude it's useless. Meanwhile, if you are familiar with it, your prospects are broader, you may have to use it, and you'll see how it was absolutely relevant and important to know...

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