**** Matt Mahoney wrote: So a progression of useful responses to "funny videos" might be:
1. Retrieving videos that other people have rated as funny (not AI). 2. Looking at videos and deciding which ones are funny (a hard AI problem). 3. Creating new, funny video (a harder AI problem). Google is still working on step 2, which doesn't require learning using creativity or exploration. Step 3 does. ***** And yet, I can easily imagine a narrow-AI approach to creating new funny videos, e.g. 1 -- make an image-processing system that can map out objects and relationships in a video [e.g. fall_in(dog, toilet) ... fall_in(pig, lake) ... ] 2 -- run a machine learning algorithm on the relation-sets extracted from videos, with the goal of learning rules distinguishing funny from unfunny videos 3 -- write a program to generate animated videos from sets of relationships [e.g. to go from fall_in(dog, toilet) to an animation of a dog falling in a toilet] 4 -- use the rules learned in Step 2 to generate new videos [possible e.g. if the rules embody a probability distro; then Step 4 is Bayesian instance generation...] A system like this may be constructible without any kind of deep AGI or insight into humor. It might not work perfectly, but humans' sense of humor is not perfect either. Yet it would lack any real insight or originality. And it would only do this one application, without ability to generalize. We have not yet plumbed the full depths of narrow AI, I feel. Nowhere near. -- Ben G ----- This list is sponsored by AGIRI: http://www.agiri.org/email To unsubscribe or change your options, please go to: http://v2.listbox.com/member/?member_id=231415&user_secret=e9e40a7e
