Hi, * AGI should be scalable - More data just mean the potential for more accurate results. * More data can chew up more computation time without a benefit. ie If all you want to do is identify a bird, it's still a bird at 1 fps and 1000 fps. * Don't aim for precision, aim for generality. Eg. AGI "KNOWS" 1000 objects. If you test to see if your object is a bird, and it is not, you still have 999 possible objects. If you test if it is an animal, you can split your search space in half - you've reduce the possibilities to 500. Successive generalisation produce accuracy, sometimes referred as a hierarchical approach.
On Fri, 2010-06-18 at 14:19 -0400, David Jones wrote: > I just came up with an awesome idea. I just realized that the brain > takes advantage of high frame rates to reduce uncertainty when it is > estimating motion. The slower the frame rate, the more uncertainty > there is because objects may have traveled too far between images to > match with high certainty using simple techniques. > > So, this made me think, what if the secret to the brain's ability to > learn generally stems from this high frame rate trick. What if we made > a system that could process even high frame rates than the brain can. > By doing this you can reduce the uncertainty of matches very very low > (well in my theory so far). If you can do that, then you can learn > about the objects in a video, how they move together or separately > with very high certainty. > > You see, matching is the main barrier when learning about objects. But > with a very high frame rate, we can use a fast algorithm and could > potentially reduce the uncertainty to almost nothing. Once we learn > about objects, matching gets easier because now we have training data > and experience to take advantage of. > > In addition, you can also gain knowledge about lighting, color > variation, noise, etc. With that knowledge, you can then automatically > create a model of the object with extremely high confidence. You will > also be able to determine the effects of light and noise on the > object's appearance, which will help match the object invariantly in > the future. It allows you to determine what is expected and unexpected > for the object's appearance with much higher confidence. > > Pretty cool idea huh? > > Dave > agi | Archives | Modify Your > Subscription > ------------------------------------------- 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=8660244-6e7fb59c Powered by Listbox: http://www.listbox.com
