From: Joscha Bach To: Ben Goertzel < >, Jeffrey Epstein <[email protected]> Subject: Re: Date: Mon, 07 Sep 2015 06:35:41 +0000 Inline-Images: running_shoppersjpg I agree w/ Joscha's caution about discrimination tasks: They can be often be solved rather well, but in devious ways, by statistical supervised learning algorithms. The attached picture will get our current best statistical methods to tell us that it sees four to six people. A really good system might recognize that two move forward and two in the opposite direction, and that the latter ones have full bags. I don't think that there is a system that would tell us that there is probably a store in the direction the bagless people are going. Most of all, current systems probably won't figure out that there must be a sniper behind that wall. People don't stop at matching patterns; they construct a conceptual world view, and integrate what they see, hear and read into it. IMHO, this is what an AI challenge needs to be about: use any kind of information, and integrate it into a deeper, growing and dynamic understanding of the world. One way of doing that might be to let it re-tell the story of a movie we show it. We will have to make sure that the particular movie is unknown to the system (it is likely going to be trained on many annotated movies), which could be achieved by picking one (or rather, several, with different degrees of difficulty) that has not aired yet when the submission is made. We might also put limits on the memory footprint of the system, to make sure that it does not memorize existing stuff too literally, but is forced to make inferences. The whole thing could be a competition, where the performance is compared to children of different ages, using a mixed jury including developmental psychologists, computer scientists and screenwriters. Prices could be given to contributions that match the performance of a 3yr old, 6yr old, and adult, for a challenge of five movie