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Structure and Interpretation of Computer Programs ~ Video Lectures by Hal Abelson and Gerald Jay Sussman PART 1
Duration:
27 minutes and 42 seconds
Country:
United States
Language:
English
License:
CC - Attribution Share Alike
Genre:
Instructional
Producer:
Hewlett-Packard Television
Director:
by Hal Abelson and Gerald Jay Sussman
Views:
680
(88
embedded)
Posted by:
dominick on Dec 4, 2008
TBA
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Video Transcription
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- I'd like to welcome you to this course on computer science.
- Actually it's a terrible way to start.
- "Computer Science" is a terrible name for this business,
- first of all, it's not a "science",
- it might be "engineering" or it might be "art",
- but I actually see that computer, so-called science, has a lot in common with magic.
- And you will see that in this course.
- So it's not a science, it's also not very much about computers.
- And it's not about computers in the same sense that physics is not really about particle accelerators.
- and biology is not really about microscope and petri dishes.
- and it's not about computer in the same sense that geometry is not really about using surveying instrument.
- In fact, there is a lot of commonality between computer science and geometry.
- Geometry, first of all, is another subject with a lousy name.
- For the name comes from gaia, meaning the Earth, and metro- meaning 'to measure',
- Geometry originally meant measuring Earth, or surveying
- And the reason for that was that thousands of years ago, the Egyptian priesthood developed the rudiment of geometry
- in order to figure out how to restore the boundaries of fields that were destroyed by the annual flood of the Nile.
- And to the Egyptians who did that, Geometry really was the use of surveying instruments.
- Now the reason that we think computer science is about computers
- is pretty much the same reason the Egyptians thought Geometry was about surveying instruments
- and that is, when some field is just getting started and you don't really understand it very well
- its very easy to confuse the essence of what you're doing with the tools that you use
- and indeed, on some absolute scale of things we probably know less
- about the essence of Computer Science than the ancient Egyptians really knew about Geometry.
- Well what do I mean by the "essence" of Computer Science, what do I mean by the "essence" of Geometry?
- See it's certainly true that these Egyptians went off and used surveying instruments
- but when we look back on them after a couple of thousand years, we say gee,
- what they were doing, the important stuff they were doing, was begin to formalize
- notions about space and time, to start a way of talking about mathematical truths formally.
- That led to the axiomatic method, that led to sortof all of modern mathematics.
- Figuring out a way to talk precisely about so-called "declarative knowledge,"
- "What is true."
- Well similarly, I think in the future, people will look back and say
- yes, those primitives in the 20th century were fiddling around with these gadgets called computers,
- but really what they were doing was starting to learn how to formalize
- intuitions about "process," how to do things.
- starting to develop a way to talk precisely about "how-to" knowledge
- as opposed to Geometry, which talks about "what is true."
- Let me give you an example of that.
- Here is a piece of mathematics that says what a square root is.
- The square root of x "is" the number y such that y squared is equal to x
- and y is greater than zero. now that's a fine piece of mathematics
- but just telling you what a square root is doesn't really say anything about how you might go out and find one.
- So let's contrast that with a piece of "imperative knowledge," how you might go out and find a square root.
- This in fact also comes from Egypt, not ancient ancient Egypt, this is an algorithm due to Heron of Alexandria
- called "How to Find a Square Root by Successive Averaging," and what it says is
- that in order to find a square root, you make a guess, you improve that guess
- and the way you improve the guess is average the guess and x over the guess (and we'll talk a little later about why that's a reasonable thing)
- and you keep improving the guess until its good enough. that's a method, "how to do something,"
- as opposed to declarative knowledge, that says what you're looking for. its a "process."


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