I strongly believe that the best way to AGI (Artificial General Intelligence) is building narrow AI and then gradually extend it toward more and more General Intelligence.
Finally, I implemented some of my AI techniques in real-life web site PostJobFree.com.
Now PostJobFree.com intelligently calculates Daily Job Posting Limit. The calculations are based on how many times recruiter's postings were viewed, and how many times these postings were reported as spam.
I cannot claim that this feature has "advanced intelligence", but it is intelligent nevertheless.
Here are intelligent techniques we used to build that feature:
1) Preprocessing data prior to using it in decision making.
Row data is coming in the form of "page views" and "spam report clicks".
Special process raw input into RecruiterRating and JobRating tables.
The most recent data is usually more valuable for decision making.
That's why yet another PostJobFree process makes sure that old data is slowly losing it's value (and disappears if the value is too low).
We implemented it by simply decreasing values in some columns in RecruiterRating and JobRating tables by 1% every night.
Here's what I've learned from implementing my first real-life intelligent feature:
1) The best working formulas and algorithms are relatively simple.
2) Still it takes time to carefully propose, test, chose, and implement intelligent algorithm.
3) If the system is designed properly - performance is not an issue.