On Wed, Aug 28, 2013 at 4:30 PM, Chris de Morsella <cdemorse...@yahoo.com>wrote
> If X = Y AND Y = Z then X = Z This is also logically true, but also has > no substantial bearing on how the dynamic processes by which the mind > arises from the 86 billion neuron and 100 trillion connection two phase > (electro-chemical) network that comprises our brain > Big numbers don't impress me because computer technology has some big numbers too, and 100 trillion is no closer to being infinite than the number 1 is. > > >You cannot show definitive causality for most of what goes on in most >> of the universe. >> > >> >> You just figured that out? Physicists have been telling us that some >> things happen for no reason (are random) for nearly a century. >> >> > AND when did I say random? > "You cannot show definitive causality for most of what goes on in most of the universe", and if something has no cause then by definition of the word its random. > I am not referring to random events, > Then you're referring to something that is deterministic. > I was describing the difficulty in tracing causality back from an outcome > state Y to an originating (within the frame of reference) state Y. > Then you're describing something that is difficult. > I was making the statement that because of the chaotic and highly > parallelized nature of the brain that very often the attempt to work back and > determine the causes is in practice impossible. > And because of the chaotic and highly parallelized nature of a supercomputer in practice it is impossible for a human to determine all reasons that caused it to tell us that the 10 trillion's digit of Pi is the number "1". So what's your point? > Now hopefully you will finally figure out what I have being trying to > communicate to you and realize that my stating that it is impossible to > work back from result X to initial state Y by trying to rewind events and > work back step by step is not the same thing as saying that the outcome X > is the result of some random process. > Well of course it's not the same thing as saying that the outcome X is the result of some random process! To be deterministic a event must have a cause, but it is not necessary for Chris de Morsella to know that cause. However if no cause exists for Chris de Morsella to know then its random. > The brain is not a random state machine, > If it was the brain would be pretty damn useless except as a hardware random number generator, and I can buy one of those for $20. > it has a definite direction of flow and we experience a clear and > consistent outcome. > And that is why when somebody behaves oddly in a way we don't understand we say "why did you do that?", we demand to know the cause of their action. If they say "I did it for no reason" we tend to think they are a bit demented and their action UNREASONABLE. > > Watson was based on self learning algorithms > Yes, Watson was constructed in such a way that it was capable of extracting facts from its environment, and if its method for doing this were not deterministic what it would be extracting would not be facts but gibberish. > To characterize a self-learning machine that "learned" what associations > -- and what meta-associations as well -- because it is often on the meta > information that algorithms operate -- as an example of determinism is > really stretching it. > Exactly what is being stretched? For all the trillions of facts that Watson knew there was a reason it knew every one of them, even if it was too complex for 3 pounds of grey goo inside the head of a certain type of bipedal hominid to follow the very long logical train of thought. > Watson was so astoundingly successful on Jeopardy precisely - -I would > argue -- because it adopted a non-linear and non-directed approach. > OK, what's your point? Watson was able to demonstrate a remarkable ability to associate a correct > answer from a Jeopardy question based on a very rapid lookups in its vast > generalized store of knowledge. OK, what's your point? > Watson was so successful -- precisely because it did not attempt to > impose any deterministic algorithms, > That is ridiculous, hardware random number generators can't do what Watson did! > > The key term & methodology: is in fact SELF-LEARNING, which by > definition is not pre-determined. > So what? Turing proved almost 80 years ago that causality does not necessarily mean you can determine what it will do even in principle, much less in practice. In general if you want to know if a 100% deterministic Turing Machine will ever stop all you can do is watch it and see, and you might be watching quite literally forever. >>>>I never claimed we would someday understand how to make an AI more >>>> intelligent than ourselves, I only said that someday such an AI would get >>>> made. >>>> >>> >> > >>> And how are you sure it has not already been achieved. > > >> > >> Because computers don't rule the world. Yet. > > > > And you "know" this how? > You're still alive. >>>What I said about needing to understand that which you are studying in >> order to be able to really be able to manipulate, extend, emulate, simulate >> etc. is not only true -- as you admit >> > >> > >> I don't admit that at all! it is sufficient but not necessary. >> > > > I begin to gather you are the type who will never admit anything. So be > it. > Actually I pride myself on freely admitting it when I'm wrong and not to toot my own horn but I have become rather good at it, I've had a lot of practice. So that I can thank you for educating me and correcting my error please tell me when I said you must understand something to use it, and more specifically please tell me when I said if humans don't understand how to make a AI then a AI will never get made. I am confused. What do you mean we don't understand what machines are doing? > Which word didn't you understand? > We do though -- to a large degree and to a fine degree of detail -- > understand how software systems are working > And that's why software always works exactly how we want it to. > even in the dynamic dimensions of a given operational instance. > You can understand any given computer operation, but you can not understand every computer operation. > we do have a very good general idea of how it is all working and how to > ensure that the outcomes that are being generated are of a high fidelity > and have predictive value. > I am sure you have had the experience of installing a new large program on your computer and noticing that it's just sitting there and isn't doing anything, or at least it doesn't seem to be doing anything, you aren't sure. Maybe its doing important stuff and you should just give it more time, and maybe its stuck in a infinite loop and you should reboot; even if you could look into the computer's chips and read their memory state in hexadecimal it probably wouldn't help you much in deciding on what to do. >> It is entirely possible that we will never understand the fine grained >> workings of the brain, but that won't matter because the computers will >> understand it. >> > > > And you sate this based on what assumptions? > The fact not assumption that the very fastest signals in the brain move at about 100 meters a second and many are far slower, and the fact not assumption that the speed of light is 300,000,000 meters a second. John K Clark -- You received this message because you are subscribed to the Google Groups "Everything List" group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. 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