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Youtube Killed the TV Star: How Online Video is Replacing TV

posted by cmn32480 on Wednesday January 13 2016, @11:23AM   Printer-friendly
from the cord-cutters-ftw dept.

Phoenix666 writes:

The average American watches more than five hours of TV per day, but pretty soon that leisure time may be dominated by YouTube and other online video services.

In an address at CES 2016, YouTube's chief business officer Robert Kyncl argued that digital video will be the single biggest way that Americans spend their free time by 2020 – more than watching TV, listening to music, playing video games, or reading.

The amount of time people spend watching TV each day has been pretty steady for a few years now, Mr. Kyncl pointed out, while time spent watching online videos has grown by more than 50 percent each year. Data from media research firm Nielsen shows that it's not just young people watching online videos, either: adults aged 35 to 49 spent 80 percent more time on video sites in 2014 than in 2013, and adults aged 50 to 64 spent 60 percent more time on video sites over the same time period.

Why the shift?

Original Submission

 
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  • (Score: 0) by Anonymous Coward on Wednesday January 13 2016, @02:59PM

    by Anonymous Coward on Wednesday January 13 2016, @02:59PM (#289072)

    Textbook programming also simplifies by ignoring "irrelevancies". Typical algorithm textbook pseudocode has no worries about types, overflow, array sizes and bounds. heap space, or I/O. The Turing Machine's tape is infinite. And I have found that can lead to errors. For instance, Quicksort is always stated to take time O(n log n) (on average, worse case is O(n^2)), but that makes a big assumption, which is that a single comparison can be done in O(1). Yet string comparison is well known to take O(n) time. How can Quicksort be done in O(n log n) time on strings?

    Wait, the time to compare two strings in the collection depends on the number of strings in the collection?

    If you have a collection of nstrings strings whose average length is ncharacters per string, then the sorting time is O(nstrings log nstrings), but O(ncharacters per string). Note the different variables in the big-O notation. You can change the average length of the strings in your collection independently of the size of the collection. You can have a collection of 20 strings, each a million characters long, or a collection of a million strings, each 20 characters long. While the total number of characters is the same, the sorting time for both will differ dramatically.

  • (Score: 2) by bzipitidoo on Wednesday January 13 2016, @03:30PM

    by bzipitidoo (4388) Subscriber Badge on Wednesday January 13 2016, @03:30PM (#289087) Journal

    Yes, you spotted the main trick to that trick question, different n's :).

    And yet, the two quantities are not completely unrelated. As the number of strings grows, the match length also grows. Supposing you have an alphabet of 26 letters, and 27 strings to sort. At least 2 of the strings must start with the same letter. With 26^2+1 strings to sort, that grows to 2 matching letters at the start for at least 2 of the strings.