Wow, sorry about that. I am using firefox and had no problems. The site was just the first reference I was able to find using google.
Wikipedia references the same fact: http://en.wikipedia.org/wiki/Feedforward_neural_network#Multi-layer_perceptron On Tue, Aug 19, 2008 at 3:42 AM, Brad Paulsen <[EMAIL PROTECTED]> wrote: > Abram, > > Just FYI... When I attempted to access the Web page in your message, > http://www.learnartificialneuralnetworks.com/ (that's without the > "backpropagation.html" part), my virus checker, AVG, blocked the attempt > with a message similar to the following: > > Threat detected! > Virus found: JS/Downloader.Agent > Detected on open > > Quarantined > > On a second attempt, I also got the IE 7.0 warning banner: > > "This website wants to run the following add-on: "Microsoft Data Access - > Remote Data Services Dat...' from 'Microsoft Corporation'. If you trust the > website and the add-on and want to allow it to run, click..." (of course, I > didn't click). > > This time, AVG gave me the option to "heal" the virus. I took this option. > > It may be nothing, but it also could be a "drive by" download attempt of > which the owners of that site may not be aware. > > Cheers, > > Brad > > > > Abram Demski wrote: >> >> Mike, >> >> There are at least 2 ways this can happen, I think. The first way is >> that a mechanism is theoretically proven to be "complete", for some >> less-than-sufficient formalism. The best example of this is one I >> already mentioned: the neural nets of the nineties (specifically, >> feedforward neural nets with multiple hidden layers). There is a >> completeness result associated with these. I quote from >> http://www.learnartificialneuralnetworks.com/backpropagation.html : >> >> "Although backpropagation can be applied to networks with any number >> of layers, just as for networks with binary units it has been shown >> (Hornik, Stinchcombe, & White, 1989; Funahashi, 1989; Cybenko, 1989; >> Hartman, Keeler, & Kowalski, 1990) that only one layer of hidden units >> su ces to approximate any function with finitely many discontinuities >> to arbitrary precision, provided the activation functions of the >> hidden units are non-linear (the universal approximation theorem). In >> most applications a feed-forward network with a single layer of hidden >> units is used with a sigmoid activation function for the units. " >> >> This sort of thing could have contributed to the 50 years of >> less-than-success you mentioned. >> >> The second way this phenomenon could manifest is more a personal fear >> than anything else. I am worried that there really might be partial >> principles of mind that could seem to be able to do everything for a >> time. The possibility is made concrete for me by analogies to several >> smaller domains. In linguistics, the grammar that we are taught in >> high school does almost everything. In logic, 1st-order systems do >> almost everything. In sequence learning, hidden markov models do >> almost everything. So, it is conceivable that some AGI method will be >> missing something fundamental, yet seem for a time to be >> all-encompassing. >> >> On Mon, Aug 18, 2008 at 5:58 AM, Mike Tintner <[EMAIL PROTECTED]> >> wrote: >>> >>> Abram:I am worried-- worried that an AGI system based on anything less >>> than >>> the one most powerful logic will be able to fool AGI researchers for a >>> long time into thinking that it is capable of general intelligence. >>> >>> Can you explain this to me? (I really am interested in understanding your >>> thinking). AGI's have a roughly 50 year record of total failure. They >>> have >>> never shown the slightest sign of general intelligence - of being able to >>> cross domains. How do you think they will or could fool anyone? >>> >>> >>> >>> ------------------------------------------- >>> 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/?&; >>> Powered by Listbox: http://www.listbox.com >>> >> >> >> ------------------------------------------- >> 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/?&; >> Powered by Listbox: http://www.listbox.com >> > > > ------------------------------------------- > 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/?&; > Powered by Listbox: http://www.listbox.com > ------------------------------------------- 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=111637683-c8fa51 Powered by Listbox: http://www.listbox.com
