Rules, policies, everywhere a statement, everywhere a sentence. How we agree on rules: parliamentary procedure -- a vocal editing of text.
How we learn rules: we read or hear their statement, or we infer the local custom, by observing the examples. How do we implement rules: with love for safety and co-operation, we enact them in ourselves, for those that don't self-discipline with policy enforcement officers, a reminder of the fear of disorder. How are rules used: For safety, for co-operation. For communication. Text, text, text, it's what we revolve around, not here, not there, but everywhere, we find it. Poetically, Logan On Tue, Dec 8, 2015 at 7:39 PM, Jim Bromer <[email protected]> wrote: > I think I understand what you are getting at, and it makes a lot of > sense. You and Aaron have convinced me that I should spend more time > working on my AI / AGI project but unfortunately I still do not seem > to have the time to work on it. > > I think I do have some good ideas about things like artificial > imagination which is important. And curiosity is something that I > always felt was easy. > Jim Bromer > > > On Sun, Dec 6, 2015 at 3:41 PM, Stanley Nilsen <[email protected]> > wrote: > > Thanks for giving this some thought Jim. I'm going out of town for a few > > days, so don't consider silence to be a loss of interest. > > > > One of your comments was: > > > > "But the program has to be able to develop its > > own strategies to 'evaluate' some things because that is a good > > strategy for a computer program to use - in some cases. And the > > usefulness of logical 'evaluation' implies that some strategy for > > evaluating conceptual relationships other than simple numerical > > methods would also be a good strategy to use." > > > > --------------------- > > My problem with the program developing "it's own strategy to > evaluate..." is > > that strategy is not a strength of a child. Somehow children acquire the > > ability to put 2 and 2 together, but we haven't discovered how to get a > > machine to do it. What's the machine equivalent of curiosity? I'm not > > convinced that we have an adequate "big" picture to see how the pieces > will > > eventually fit together. > > > > The big picture looks kind of like "design and make a system that works, > > even if one needs to, substitute human effort for some of the > components." > > Then, when the system is in place, determine how to remove more and more > of > > the human element. Eventually one is left with a system that may > interface > > with humans but only as though using them as a resource. > > > > By the way, I think a text only approach is a good start. I'm > interested in > > looking at the use of words as a way to convey "benefit." Initial > design is > > interesting because there are so many words and phrases to choose from. > I > > get it that this sounds like a chat bot, but for me it's a way of > > experimenting with the idea of a benefit driven system. > > > > Stan > > > > > > > > On 12/06/2015 09:17 AM, Jim Bromer wrote: > >> > >> You might be able to think of ways to benefit the poor but you would > >> have a lot of trouble to implement them. You might be able to help a > >> few people but if you are like most of the rest of us that would be > >> it. > >> > >> So you think that there are a lot of opportunities to use basic > >> implementation strategies to get the AI/AGI program to do something > >> that would be beneficial in some way? But the only problem that you > >> foresee is the coding? But why would that be difficult? For example, I > >> think that I could develop a prototype of an AGI program using text > >> only. If you start with something like that then it would be simple to > >> get started because you can find code that contains the basic forms > >> for text IO. The problem that I am having is that even when I strip > >> the plan down to what I think would be a minimum for a simple database > >> management program (of my own design) it still cannot be done on the > >> little time I have to code, and without any reason to believe that I > >> could get past something that would not work too well I don't have > >> much commitment to get going on it. > >> > >> You said: > >> "Values (rules about values) come into play as the AGI picks the next > >> thing to do. But, we already know that early AGI doesn't have a > >> "values" structure to refer to. To program one is really not much of > >> an option - it is too complex to "calculate" what the value of > >> something is. To test the validity of my statement that it is too > >> complex to calculate, try it. Imagine that you are writing this into > >> code!" > >> > >> I have tried to imagine writing that into code! (Why wouldn't I have > >> tried to imagine that?) But the program has to be able to develop its > >> own strategies to 'evaluate' some things because that is a good > >> strategy for a computer program to use - in some cases. And the > >> usefulness of logical 'evaluation' implies that some strategy for > >> evaluating conceptual relationships other than simple numerical > >> methods would also be a good strategy to use. But this would be > >> complicated. I think the opportunities that you mentioned would be > >> difficult to code as well - if you wanted to avoid getting bogged down > >> in code that is good for narrow-AI. The problem is that once you make > >> the commitment to do something that is effectively narrow-AI then > >> there are all sorts of enticing shortcuts that become available but > >> that you really need to keep to a minimum. > >> > >> Using a text-only program that has to start so that it can only act on > >> the simple 'opportunities' (or 'low hanging fruit') of text (and > >> conversation of course) is where I would start. But it should be clear > >> that I don't want to take all the shortcuts that sort of situation > >> would offer. So I want my program to 'look' for opportunities on its > >> own so to speak. It may not be possible for a program to do that at a > >> very sophisticated level from our point of view, but we know that > >> computer programs are good at some things that we are not so good at. > >> So, my point of view is that the program should be able to pick up all > >> sorts of patterns (opportunities) that we would miss so that is where > >> I want to start at. Having thought about that I concluded that it > >> would have to be looking at the recombination of all sorts of odd > >> kinds of data in order to find a few combinations that might be > >> useful. > >> Jim Bromer > >> > >> > > > > > > > > ------------------------------------------- > > AGI > > Archives: https://www.listbox.com/member/archive/303/=now > > RSS Feed: > https://www.listbox.com/member/archive/rss/303/24379807-653794b5 > > 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/303/5037279-a88c7a6d > 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/303/21088071-f452e424 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-58d57657 Powered by Listbox: http://www.listbox.com
