10 Hamming, Learning to Learn: Coding Theory I, 18 April 1995
Channel: Hamming on Hamming: Learning to Learn
Date: 22/02/2018

Having looked at computers and how they operate, we now turn to the problem of the representation of information - how do we represent the information we want to process. Recall that any meaning that a symbol may have depends on how it is processed; there is no inherent meaning to the bits that the machine uses. In the synthetic language mentioned in Lecture 4 on the history of software, the breaking up of the instructions was pretty much the same for every code instruction and this is true for most languages; the "meaning" of any instruction is defined by the corresponding subroutine.

00:00 Introduction
01:49 Source Illustration
07:05 Transmission through space and time are really the same kind of problem
08:09 Getting another bit or decimal digit is very expensive
08:40 What we are resorting to is coding theory to escape doing things right
09:00 symbols need not be the same length
15:03 Unique instantaneously decodable codes
15:49 Two Examples: 5 Symbols
21:28 Kraft at Bell labs
24:59 Exit symbol: When am I done?
26:50 How the unique decode-ability works in proof
32:17 Just because it satisfies the craft and equality does not mean it’s a uniquely decode-able instantaneous code.
33:26 Communication of symbols
34:38 Discussion of the next lectures
35:26 Information theory
40:38 We have never proved that arithmetic is consistent
41:11 Our words have variable meaning
43:31 Once you put something into words that is what you believe
48:51 End

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