I have stated this previously to the AGI community and think that the way to go is that QA recommendation engines will be the first killer app for AGI. Not recommendation like the ones you see now with the "others who bought...", but ones that look more like "concierge" QA services.
From what I understand from speaking with Selmer Bringsjord, Bloomberg has an outstanding internal QA system, so there is progress, the trouble is that it's all behind corporate firewalls.
There was a silly little online game that came out a few years ago called Akinator [1] that would "guess" a public personality and did so by "learning" based on user inputs - very naiive implementation of CTL but gets the gist of how you can implement a mock AI to get damn good results.
If you did a little delphi to stack the initial deck of results, say for a car buying QA recommendation service, I think you could have a pretty powerful tool that could be replicated across services.
From what I understand from speaking with Selmer Bringsjord, Bloomberg has an outstanding internal QA system, so there is progress, the trouble is that it's all behind corporate firewalls.
There was a silly little online game that came out a few years ago called Akinator [1] that would "guess" a public personality and did so by "learning" based on user inputs - very naiive implementation of CTL but gets the gist of how you can implement a mock AI to get damn good results.
If you did a little delphi to stack the initial deck of results, say for a car buying QA recommendation service, I think you could have a pretty powerful tool that could be replicated across services.
[1]http://en.akinator.com/