5 ms·

Yes, you can also practice swimming without water.

Delk 6y ago
I don't think that's an entirely fair comparison. You can design algorithms and prove things about them without hardware, and the algorithms and their properties will be valid in and of themselves. You don't get to "swim", but the algorithms will be there. One could argue that "computer science" is the study of the logical processes involved in computation.
bawolff 6y ago
"[Computer science] is not really about computers -- and it's not about computers in the same sense that physics is not really about particle accelerators, and biology is not about microscopes and Petri dishes...and geometry isn't really about using surveying instruments. Now the reason that we think computer science is about computers is pretty much the same reason that the Egyptians thought geometry was about surveying instruments: when some field is just getting started and you don't really understand it very well, it's very easy to confuse the essence of what you're doing with the tools that you use." -- Hal Abelson (1986)
- andi999 6y ago
  While this quote was good at its time, I don't think it aged well. It is 35 years later, and I do not think the here called essence has appeared.
  - bawolff 6y ago
    When was the last interesting computer science paper you read where the computer code or the instantiation of it onto a physical machine was the interesting part of the paper?
    - andi999 6y ago
      Na. If one follows the comparison with physics: the subject is about what is taught to undergrads (they do not get taught building particle accelerators) but the essence of physics. So if I use the test what do professors believe is the essence of the field, you get something like: http://catalog.mit.edu/degree-charts/computer-science-engineering-course-6-3/ http://catalog.mit.edu/degree-charts/computer-science-engine... And the computer science part is: Computation Structures 12 6.006 Introduction to Algorithms 12 6.009 Fundamentals of Programming 12 6.031 Elements of Software Construction 15 6.033 Computer Systems Engineering (CI-M) 12 6.034 Artificial Intelligence 12 or 6.036 Introduction to Machine Learning 6.045[J] Computability and Complexity Theory 12 or 6.046[J] Design and Analysis of Algorithms I would say all but (maybe) the last two (one) are about computers (maybe the first one in between). I just picked MIT as a random example, just to illustrate my general impression.
      - bawolff 6y ago
        Why do you think the essence of a subject is what is taught in undergrad (doubly so in CS where the emphasis is employability in industry and not research in computer science) Is the essence of math calculus? That gets shoved down undergrad throats. It is even an important subfield of mathematics. But its hardly the essence.
        andi999 6y ago
        What school teaches mostly calculus to math undergrads? I mean, let's do the same comparison with math, again MIT: https://math.mit.edu/academics/undergrad/major/course18/pure.php https://math.mit.edu/academics/undergrad/major/course18/pure... Required Subjects 18.03 or 18.032 (formerly 18.034) (Differential Equations) [sufficiently advanced students may substitute 18.152 or 18.303] 18.100 (Real Analysis) 18.701 (Algebra I) 18.702 (Algebra II) 18.901 (Introduction to Topology) One of the following three Subjects 18.101 (Analysis and Manifolds) 18.102 (Introduction to Functional Analysis) 18.103 (Fourier Analysis — Theory and Applications) Personally I think this is a good impression on math of course in research you cannot do what is know already, but I would say, if any of these subjects above would be not already fully developed there would be researched today, so basically the undergrad covers an essential part of what we know (have researched) which I do not think people would say ah come on today one wouldnt research this (if not for the reason of course that the research has been done)
avz 6y ago
Developing complexity theory of quantum algorithms without a quantum computer is not any more outrageous than developing complexity theory of Turing machines with oracles. The former might a least be built one day. And yet, people produce interesting research on both. Turns out water is overrated (as far as complexity theory goes).

Delk 6y ago

I don't think that's an entirely fair comparison. You can design algorithms and prove things about them without hardware, and the algorithms and their properties will be valid in and of themselves. You don't get to "swim", but the algorithms will be there. One could argue that "computer science" is the study of the logical processes involved in computation.

bawolff 6y ago

"[Computer science] is not really about computers -- and it's not about computers in the same sense that physics is not really about particle accelerators, and biology is not about microscopes and Petri dishes...and geometry isn't really about using surveying instruments. Now the reason that we think computer science is about computers is pretty much the same reason that the Egyptians thought geometry was about surveying instruments: when some field is just getting started and you don't really understand it very well, it's very easy to confuse the essence of what you're doing with the tools that you use." -- Hal Abelson (1986)

andi999 6y ago
While this quote was good at its time, I don't think it aged well. It is 35 years later, and I do not think the here called essence has appeared.
- bawolff 6y ago
  When was the last interesting computer science paper you read where the computer code or the instantiation of it onto a physical machine was the interesting part of the paper?
  - andi999 6y ago
    Na. If one follows the comparison with physics: the subject is about what is taught to undergrads (they do not get taught building particle accelerators) but the essence of physics. So if I use the test what do professors believe is the essence of the field, you get something like: http://catalog.mit.edu/degree-charts/computer-science-engineering-course-6-3/ http://catalog.mit.edu/degree-charts/computer-science-engine... And the computer science part is: Computation Structures 12 6.006 Introduction to Algorithms 12 6.009 Fundamentals of Programming 12 6.031 Elements of Software Construction 15 6.033 Computer Systems Engineering (CI-M) 12 6.034 Artificial Intelligence 12 or 6.036 Introduction to Machine Learning 6.045[J] Computability and Complexity Theory 12 or 6.046[J] Design and Analysis of Algorithms I would say all but (maybe) the last two (one) are about computers (maybe the first one in between). I just picked MIT as a random example, just to illustrate my general impression.
    - bawolff 6y ago
      Why do you think the essence of a subject is what is taught in undergrad (doubly so in CS where the emphasis is employability in industry and not research in computer science) Is the essence of math calculus? That gets shoved down undergrad throats. It is even an important subfield of mathematics. But its hardly the essence.
      - andi999 6y ago
        What school teaches mostly calculus to math undergrads? I mean, let's do the same comparison with math, again MIT: https://math.mit.edu/academics/undergrad/major/course18/pure.php https://math.mit.edu/academics/undergrad/major/course18/pure... Required Subjects 18.03 or 18.032 (formerly 18.034) (Differential Equations) [sufficiently advanced students may substitute 18.152 or 18.303] 18.100 (Real Analysis) 18.701 (Algebra I) 18.702 (Algebra II) 18.901 (Introduction to Topology) One of the following three Subjects 18.101 (Analysis and Manifolds) 18.102 (Introduction to Functional Analysis) 18.103 (Fourier Analysis — Theory and Applications) Personally I think this is a good impression on math of course in research you cannot do what is know already, but I would say, if any of these subjects above would be not already fully developed there would be researched today, so basically the undergrad covers an essential part of what we know (have researched) which I do not think people would say ah come on today one wouldnt research this (if not for the reason of course that the research has been done)

avz 6y ago

Developing complexity theory of quantum algorithms without a quantum computer is not any more outrageous than developing complexity theory of Turing machines with oracles. The former might a least be built one day. And yet, people produce interesting research on both. Turns out water is overrated (as far as complexity theory goes).