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the user critic isn't really scalable so much as a learning thing. users
start uneducated and as more of them attend the movie (or read the book
etc) the community "learns" to like or dislike. individuals may still
diverge, but the community opinion tends to a conclusion.
it's an important part of ai (and the basis of neural nets) but i'm not
sure it's a scalable technology as most of us would think of it.
in most cases a "scalable" technology is accepted as one where the cost
(whatever that might mean) grows as n(log n). ie less than linear.
this applies across a wide range of disciplines, especially economics of
scale - and helps to explain why us small guys can be innovative, but
not competitive ;)
Roger L. Costello wrote:
> Hi Folks,
> A few musings about "scaling" which I thought might be of interest ...
> Note: In this message I use the word "technology" in its broadest
> sense. It can mean a specific tool, or it can mean an approach or
> A key aspect of the Web is its ability to scale. Web technologies
> flourish or die depending on their ability to scale.
> What does it mean for a technology to scale? What does it mean that a
> technology does not scale?
> To have a sensible net-centric vision it is critical to have a deep,
> intuitive understanding of this concept of scaling. As a company
> moves to a net-centric environment it must adopt technologies that
> scale well. A technology will either scale or it will die.
> Let's consider some examples.
> A SCALABLE MOVIE REVIEW TECHNOLOGY
> Roger Ebert is a professional movie critic. He reviews a movie and
> then provides information about it:
> - a short description
> - a rating (1 - 4 stars)
> [Note that what Ebert provides is "metadata" about the movie]
> Over the years, the number of movies has multiplied (independent
> movies, blockbuster movies, etc). It is no longer possible to Ebert
> to review all them.
> Having a single professional movie critic review movies doesn't
> scale. Even a group of professional movie critics would be soon
> As well as not scaling, there is a problem with "truth". A movie
> review represents someone's interpretation, not facts. Everyone has
> their own opinions about a movie. Ebert may love the movie, but the
> rest of the world may hate it.
> An alternative to using a professional movie critic to review movies
> is to have each movie producer generate a movie review. This approach
> scales well - there is one movie reviewer for each movie. Of course,
> the problem with this approach is that the movie review will be
> heavily biased.
> A third alternative is to record the comments of the movie-goers.
> This approach is highly scalable - there are many reviewers for each
> movie. Further, since there are many reviewers there is a diversity
> of opinions, which give a variety of perspective to someone who is
> trying to decide whether to view a movie.
> Thus, a scalable movie review "technology" is one that can grow as the
> number of movies to be reviewed increases.
> A SCALABLE BOOK REVIEW TECHNOLOGY
> The New York Times has a small group of book reviewers. This group
> reviews books and then publishes their reviews.
> Just as with the problem of reviewing movies, using professional
> reviewers does not scale. The New York times group is unable to
> review the exponentially growing number of new and old books.
> An alternative approach is for each book author to elicit a review
> from a fellow author. This scales well, but suffers from bias.
> A third alternative is to let the users (the readers) provide a review
> of the books. This scales well and provides for a diversity of opinions.
> A scalable book review "technology" is one that can grow as the number
> of books to be reviewed increases.
> LESSONS LEARNED
> There are some lessons to be learned from the above examples. There
> are three approaches to solving a problem:
> 1. The high priests approach: Solve the problem using a small,
> centralized set of
> skilled professionals (the professionals may be geographically
> separate but
> functionally they are centralized)
> 2. The authors approach: Solve a problem using the authors.
> 3. The users approach: Solve the problem using the large body of
> distributed users.
> The high priests approach is not scalable, although it may produce
> precise, reliable results.
> The author approach is scalable, but it may produce dubious results.
> The user's approach is scalable and produces multiple results which
> are then shared.
> A SUCCESSFUL WEB TECHNOLOGY
> A successful web technology is one that:
> - scales and
> - shares
> Technologies that scale invite participation by the users. When the
> users become the professionals then the technology has succeeded:
> - When your users style the XML data to their own liking and share
> their stylesheets with others, then your technology for making
> appealing looking data has succeeded.
> - When your users markup data using tags that make sense to them and
> share their tags with others, then your markup technology has succeeded.
> - When your movie goers write reviews of movies and post them for
> others to view, then your movie review technology has succeeded.
> - When your book readers write review of books and post them for
> others to view, then your book review technology has succeeded.
> A long time ago (Oct. 28, 2003) John Cowan made the below remark on
> xml-dev. I now understand it.
> Roger L. Costello scripsit:
>> BTW John, I really liked your paradigm shift on the telephone
> operator story.
>> Can you think of a similar shift with programming? /Roger
> Yes, in fact. Perhaps ten years ago, I was sitting next to a stranger
> on the New York to Boston shuttle. In casual conversation, she asked
> me what I did. "I'm a computer programmer", said I. She said, not
> unusually, "Oh, I don't know anything about programming", but then
> added in the same breath "except for some Excel and Basic." I had
> an epiphany: the world had changed.
> As always, comments are welcome. /Roger
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