--- "YKY (Yan King Yin)" <[EMAIL PROTECTED]> wrote:

> For those using database systems for AGI, I'm wondering if the data
> retrieval rate would be a problem.

I analyzed the scalability of distributed indexing for my thesis (linked at
http://www.mattmahoney.net/agi.html ).  For data randomly distributed in a
vector space model up to log n dimensions, storage is O(n log n), retrieval
time is effectively O(log n) and update is O(log^2 n).  In practice you can do
better because data tends to cluster, reducing the effective number of
dimensions, and because accesses tend to be distributed nonuniformly.  Data
accessed frequently will tend to be cached in nearby nodes.

I realize you are asking about the relational model, but you can implement the
most common transactions, e.g. retrieving or updating a small number of
records at a time, by storing records of the form "author timestamp table
field=value field=value ...".  This also gives you transaction logging,
rollback, and authentication, which will be important in any database with
lots of users (I assume AGI).  However I don't think it will be as powerful as
records of the form "author timestamp arbitrary_text".

> To use an example,
> 
> If a lot of people search for "Harry Porter", then a conventional
> database system would make future retrieval of the "Harry Porter" node
> faster.
> 
> But the requirement of the inference system is such that, if "Harry
> Porter" is fetched, then we would want *other* things that are
> associated with Harry Porter to be retrieved faster in the future, for
> example items such as "JK Rowling" or "fantasy fiction".

A huge relational database would retrieve the fact that Harry Porter won a
gold medal for the high jump in the 1908 Olympics.  A better language model
(like Google) might figure out that you meant "Harry Potter" :-)


-- Matt Mahoney, [EMAIL PROTECTED]

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