--- On Tue, 1/13/09, Mike Tintner <[email protected]> wrote: > Oh and just to answer Matt - if you want to keep doing > narrow AI, like everyone else, then he's right - > don't worry about it. Pretend it doesn't exist. > Compress things :).
Now, Mike, it is actually a simple problem. 1. Collect about 10^8 random photos (about what we see in a lifetime). 2. Label all the ones of houses, and all the ones of things flying. 3. Train an image recognition system (a hierarchical neural network, probably 3-5 layers, 10^7 neurons, 10^11 connections) to detect these two features. You'll need about 10^19 CPU operations, or about a month on a 1000 CPU cluster. 4. Invert the network by iteratively drawing images that activate these two features and work down the hierarchy. (Should be faster than step 3). When you are done, you will have a picture of a flying house. Let me know if you have any trouble implementing this. And BTW the first 2 steps are done. http://images.google.com/images?q=flying+house&um=1&ie=UTF-8&sa=X&oi=image_result_group&resnum=5&ct=title -- Matt Mahoney, [email protected] ------------------------------------------- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244&id_secret=126863270-d7b0b0 Powered by Listbox: http://www.listbox.com
