Aaron, I did not want to say anything that might be deemed overly critical after you seemed to be willing to go along with my challenge, but I get the feeling that you did not actually understand what I was doing.
I do not actually think that it is likely that I will get my program to work within a year. I was just challenging people who talk about prediction in AGI to try using it in real life, but when they do they have to be willing to accept the results of the the actual outcomes of their experiences as compared to their predictions. So while it feels like I should be able to write an AGi program within a year, I do not actually expect that I will be able to do so. So I said that if a year passes (that is if another year passes) and I still am unable to show that I have something interesting, I will have to accept the results of my experiment and recognize that the expectations that I had were not realistic...And the idea that it will just take another year aren't too likely to be realistic either - if I do not have something interesting to show for my efforts after a year (or a year and a half). Perhaps you were not able to totally get what I was actually saying because you are just skimming what I wrote. Or perhaps it is just too psychologically threatening for you to take that next step and recognize that if the programming is just too complicated to get it going in a couple of years then maybe it is just too complicated a problem for us. So if I don't succeed in a year then it will also stand as evidence that it is unlikely that you will succeed. Ok, maybe it is only weak evidence, but if you don't succeed in two years that will stand as evidence that you will be unlikely to succeed - unless you try another tack. I fully realized that people used the concept of prediction in different ways. I just don't see how that changes anything. If it is such a powerful tool then try using it in a way that is consistent with its proclaimed value. The fact that people can make predictions that do not come true then just rationalize the failure away is powerful evidence that the power of 'prediction' as an AGI tool is nonsense. It is the ability to create new ways of interpreting the evidence that drives human creatiivity, not verification through prediction or an exotic method of combining possible outcomes given the evidence of the moment into a decision process that determines the next step. Those methods are useful but all that I am saying is that the driver of intelligence is the rationally creative process. But if creativity is not used rationally then it can turn into delusion. I just found that the old salvaged program that I discarded years ago was an earlier version of the program. The more recent version was a greatly improved but it was unfinished and is too difficult to be useful to me because the bugs are multiple at many bug points. But I think I might be able to use my reviving memories of what I was trying to do back then to build a new simpler program. And with that simpler program I can begin testing some simple AI / AGi ideas that I have as I go along. And if things work out then I could make the program more sophisticated as I go along. So although I do not actually believe that I will be successful, I think that I have a better development plan than I did last time. However, the discovery that the more advanced version is just too complicated and the less advanced program not developed enough is a major set back. It is very negative evidence. This insight comes directly from the schedule and the mature recognition that a month out of a year with nothing to show is a substantial negative indicator. That is an example of how rationalism can be combined with creative insight to produce an insight of value - even though it is not an encouraging insight. How can I use this setback? I have a lot of functions that do work, and I have a lot of plans that can be implemented rather quickly. And I have the most serious mistakes that I made in the past to work with now. But I have to get the basic program going pretty quickly so I can begin some early testing of my AI / AGi ideas. Jim Bromer On Mon, Jan 21, 2013 at 4:04 PM, Aaron Hosford <[email protected]> wrote: > I'm going to make a prediction about my own project: It has taken me a > year already, just laying the foundation, and I am not done yet. I am only > just getting to the point where I can start to write and test code that > actually does things remotely comparable to verbal/symbolic thinking. Even > if I don't need to extend or completely rewrite the underlying framework > due to some unforeseen issue, I predict it will take at least another year > before I start to see any fruitful results out of the system, and more > years still before the system starts to grow beyond the AGI equivalent of > infancy. I think AGI is just too big of a problem to see instant results. > Your own attempt could be seen as an attempt to falsify that last > statement. I hope you succeed. I look forward to seeing your working AGi > program in a year's time. > > > On Mon, Jan 14, 2013 at 6:16 AM, Jim Bromer <[email protected]> wrote: > >> We are almost finished with two weeks of the new year. I said that I was >> going to make a prediction about being able to get an AGi-Lite program >> working within a year in order to demonstrate how an actual prediction like >> this can be used as the basis for drawing conclusions of the effectiveness >> of one's own theories. I agree that you cannot expect results in set >> period of time but I was able to create other useful theories based on >> using different kinds of reasoning on the prediction. The question now is >> whether or not I can accept the results of my own experiments. >> >> For instance, I said that if I was truly confident that I knew how to >> create an AGI program (even an AGi-Lite program or AGi as I called it) then >> I would be extremely motivated to get going on this project. So then, I >> reasoned, if two weeks went by and I did not even have the user interface >> done then this would be indicative that I wasn't quite as motivated as my >> hubris would suggest. Well, I took the database definitions and the user >> interface from the remains of an old program that I had abandoned then >> salvaged a number of years ago and started working on it. It was much more >> complicated than I remembered and even though I haven't been able to save >> any data with it yet, it is slowly coming back to me. So yes, I had a >> fundamental user interface within two weeks, and while that does not show >> anything about whether my AGi ideas will work or not, it does show that I >> have a fundamental enthusiasm and confidence in my theories. I have proven >> nothing about my AGi theories, but I did take one fast indication of a >> potential problem off the table. My conscious and my unconscious or >> semi-conscious impressions of what I am doing are in sync. On the other >> hand, since I did just grab a program out of the attic I should have made >> more progress than I have. Two weeks is1/26 of the way to my >> predicted goal. I also realized that I could begin making some very basic >> AGi experiments using the text on the web and I feel that I should have >> started that by now. >> >> So prediction - (including prediction as a nexus of potential progress >> overlayed with the nexus of dynamically developing plans) -is useful to >> me. I can now use the goals - the original one and the new one produced by >> a realization that I could start some initial testing using the web - to >> create a new schedule that will provide me at a tiny bit more insight into >> how my plans are starting to unfold. At this stage I haven't gotten any >> results on any AI / AGI theories but if I am able to start testing one or >> two of my ideas within the next two weeks I should have some kind of >> results to examine. One thing I did learn was that to get an advantage on >> the preliminaries it is nice to have something - that had been salvaged for >> just such a situation - to use to jump into the fun part of the puzzle a >> little faster. And that is a strategy that I can use in the next stage of >> my planning. Instead of writing a web-crawler (which is what I would like >> to do) I can just copy some text from various web pages and then paste them >> into the user interface on my salvaged program and test some elementary >> text searches to see if one of my ideas can actually be made to work. So >> based on my experiences during the first two weeks of working with a >> schedule I have developed a more efficient method of getting to the lowest >> levels of the game. I still want to write a web crawler but I can do that >> when I learn more about it. >> >> So the next two weeks: That will be 1/13 of the way to the end of the >> year. I better get going on this. (That is a familiar example of >> how prediction and using the actual results of your efforts can drive >> insight by the way). So I will like to get the bugs out of my salvaged >> program and begin testing the database operations with automated methods >> during the next 2 weeks. And I would like to conduct my preliminary text >> searches on text that I can take from selected web pages to test my >> theories about the relative words and count of those words associated with >> some key words based on whether or not the key word was (according to my >> opinion) a primary subject word or not. For instance, the word "flight" is >> found in many types of texts, but by developing frequency of use records of >> the words used along with the word "flight" I should be able to identify >> whether the text is primarily about birds or about about airplanes or about >> other sub-categories. (Although this is not a very exciting AI theory in >> this day and age, I am using it as an example of how I am able to jump into >> AI testing even though my program will take a some months to get up to >> speed.) >> >> Explanation of the Project >> I got so tired of hearing people use the word "prediction" as a basis of >> their AI/AGI theories that I decided to try using prediction in real life >> to see if was an effective method. I found, that like most other AI >> theories it worked really well in a few cases and not so well in most >> cases. However, the use of formal (declared) >> predictions gave me a surprising ability to crystallize new insight around >> the predicted events when they were compared to the event. So I tried to >> get the guys who like to use the term "prediction" in their discussions of >> AI to try this experiment themselves. Of course they could not be bothered >> with such a mundane experiment. So I challenged them: Why not use your >> predictions about your own AI/AGI projects as the basis for developing new >> insights about your theories? They would have to be able to accept the >> results of their experiments regardless of how well it worked out for them >> because it just does not make sense to believe that you have it all figured >> out if you cannot get your ideas to work year after year after year. But >> even with this aggressive challenge they still could not be bothered. So I >> decided to try it myself to show them how it might actually work. I >> predicted that I would be able to get a limited AGI program (I called it >> AGi) working within a year. I pointed out that some skeptics would not be >> convinced no matter how the program turned out but that many of my peers >> (like the less delusionally narcissistic guys in these groups) would be >> able to see that it was working if I was actually able to get it working. >> On the other hand, I explained, if I could not get my program working then >> I would have to accept the results of my experiments and recognize that I >> did not and do not have it all figured out. I do agree that an >> experimenter has to be given some leeway and there is always the >> possibility of a life-changing event interfering with the goal, but if I >> still have nothing to show after 2 years then I have to accept that >> there must be something important that I haven't figured out. It was >> explained to me that the concept of "prediction" is used in different >> theoretical ways in this group, but I was already aware of that. If you >> are using "prediction" as a basis of any kind of AI/AGI learning models, >> then you have to be able to know how to accept the results of an actual >> experiment to compare it against the predicted experiment. In an advanced >> AGI models (including the use of Bayesian Nets which I consider to be >> mundane) the potential for generating new structured relationships based on >> actual experiments is essential to the effective utilization of the model. >> This kind of effective utilization is directly related to my personal >> experience of having new insights crystallize around the predicted event >> when compared with an actual experiment. My interest though, is not in >> prediction per se but in how new structured insights crystallize. >> Jim Bromer >> *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> >> <https://www.listbox.com/member/archive/rss/303/23050605-2da819ff> | >> Modify <https://www.listbox.com/member/?&;> Your Subscription >> <http://www.listbox.com> >> > > *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> > <https://www.listbox.com/member/archive/rss/303/10561250-470149cf> | > Modify<https://www.listbox.com/member/?&;>Your Subscription > <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
