Jim, You somehow completely misunderstood what I was attempting to communicate.
Continuing... On Mon, Nov 9, 2015 at 5:35 PM, Jim Bromer <[email protected]> wrote: > Steve, > I understand what you are saying (even though the details of what you > actually write are mostly irrelevant to me). > ... which probably explains why you so misunderstood what I was communicating. > I have done many thought experiments about the AI problem. Then please post some of them, e.g. what you might say, and what you might expect in response. > Your > challenge in your last email is not something that is new to me, I > have thought about that exact question many times. However, I finally > figured out that instead of spending a lot of time trying to get you > on a higher plane of discussion I should use the opportunity to my > best advantage and try to explain my theories again. > ... and MY point was that theories be damned, that there is only one known way of extracting meaning from text at a practical rate of speed. If you can't adapt THAT, then your quest is truly hopeless. > > So the program does not need multiple IO facilities in order to > understand some things. I never said it did. I was addressing the ways that things can NOT work. That can't be simply turned around to say that doing something else WILL work. > Why don't I think that multiple IO modalities > are necessary for advancements in AI? I get that it would make a truly > advanced AI program more sophisticated but trying to use sensors and > robotics at this time would just make the contemporary programming > more difficult. The data coming in through video, for example, needs > to be analyzed before it can be used by an AI program. Stronger AI > can't just take input from multiple IO modalities and automatically > turn current AI into Strong(er) AI. > > But there is another side of the opinion that multiple IO modalities > are necessary for Stronger AI. The most obvious one is that much or > our human experience is based on multiple IO so of course a true AGI > program would have to be adaptable to different IO situations. (I > already get that.) However, the next question down is whether > different senses and IO are absolutely necessary for any AGI program. > My point was that EXPERIMENTATION is absolutely necessary to sort out the countless possible realities that spring forth from textual explanations. It is a bit difficult to do experimentation from inside a box. > To make another effort to explain this point of view I will say once > again in a new way that without certain advancements in AI no number > if IO modalities are going to make the program work the way we would > want to. So to highlight my area of interest in another way let me > just restate that I want to do some study of how the AI part of the AI > program can be improved in order to get it to work the way that I > think it needs to work. > > I don't believe that current AI / AGI methods have Conceptual > Integration methods that are sophisticated enough. > I believe that my theories on Conceptual Integration, while being > composed of methods that are mundane, should be powerful enough to > deal with many of the contemporary problems. My methods will not > produce true human-like AGI but I believe I can produce AI that human > beings will be able to communicate with using language that is much > closer to natural human language. That does not mean that the program > will be able to understand anything that is readable, but that it will > be able to work with knowledge that it has acquired and use a more > natural kind of language to communicate about it. Does that help you > to better understand what I am interested in? > I think everyone here agrees that presently known methods do NOT lead to AGI, regardless of how far you might extend them with better hardware, etc. > > I have talked about ambiguity in language many times in this group. I > am surprised that you don't remember that I did so. Perhaps you missed my thread about disambiguation being a really bad idea? > I have also talked > about the anaphoric-like reference problem. > > Simple ambiguity is a human problem. For instance, you thought I was > one of the guys who was promoting the theory that a language-based AI > program would just be able to learn from the internet. (I am not one > of those guys.) That was an ambiguity-type problem. It was also a > reference problem. You misunderstood what I was referring to when I > was talking about AI / AGI. It can be resolved by communication using > natural language unless there is something interfering with that > communication. > > However, the problem with natural language AI is that the potential > for massive ambiguity and referential confusion makes the AI problem > seem intractable. I believe that I have some good theories to deal > with that - but at the same time I realize that I am going to run up > against the knowledge complexity problem very quickly. > > So I will try to explain what I want the program to do after I have > taken a day or two to plan my response carefully and write it out as > simply as I can. > OK. I'll look for that. *Steve* =================== > > Jim Bromer > > > On Mon, Nov 9, 2015 at 3:10 AM, Steve Richfield > <[email protected]> wrote: > > Jim, > > > > OK, maybe a simple thought experiment will help. Presume for a moment > that > > the system you imagine exists here and now. You have just turned it on. > Now, > > start typing (or talking) to make it do what you want it to do: > > > > > > > > > > > > Steve > > > > On Sun, Nov 8, 2015 at 11:58 PM, Jim Bromer <[email protected]> wrote: > >> > >> Steve, > >> I do not understand how you can misunderstand what I am talking about > >> so badly since I have posted hundreds if not thousands of messages on > >> groups like this. > >> I am not planning on getting a computer program to learn by reading > >> the internet with the expectation of having it achieve human like > >> abilities. The supposition that that is what I am talking about > >> strikes me as nonsensical. > >> > >> Unfortunately, I probably will not be able to do much at all but I > >> hope to at least experiment with a higher learning mechanism that, for > >> example, can be taught through conversation. In order to achieve this > >> I am planning on using a parallel referent language which will be > >> designed to shape knowledge about some things in ways that would be > >> like rough prototypes of the kinds of ideas that I have in mind for an > >> AI / AGI program. > >> > >> I agree that in order to 'understand' text the program would need to > >> build models about reality. However, I am in total disagreement with > >> the idea that an AI program would need to have some sort of embodiment > >> to understand text about the world. Such thinking strikes me as > >> absurdly naïve. The reason is that I believe there are very basic > >> parts of AI methods that are almost totally missing in contemporary AI > >> programs and the fantasy that if you could just slap some robotics > >> onto one of these primitive AI designs then the program would > >> magically be more capable of understanding is somewhere near the > >> height of absurdity. > >> > >> So I want to try to improve on the AI programming by working on a > >> design that would be able to integrate simple knowledge or knowledge > >> about simple things together. I don't think deep learning is good > >> enough for this because deep learning neural networks have a such a > >> crude way of going about this integration of related ideas. Of course, > >> I am aware that there are other problems with complexity that are > >> difficult to work around. I have been trying to find a polynomial time > >> solution to SAT for the past few years because I thought that would > >> help me with complexity. However, I haven't been able to make any real > >> progress on that and I just don't see how the human mind could > >> possibly be using p=np in some way given the propensity of 'organic' > >> processes to generate unique manifestations of very irregular > >> patterns. > >> > >> So back to the main topic of my thought. Interactions with the sensory > >> world of human beings is not necessary for AI because the information > >> that comes in from those senses would have to be integrated well to > >> produce 'understanding' just as information that comes in through the > >> keyboard would need to be. It is my belief that smart conceptual > >> integration is an outstanding problem in contemporary AI and it is a > >> problem I can work on. > >> > >> Unfortunately I won't be able to do much work on the problem. Perhaps > >> I squandered too much time writing in groups like this and working on > >> my p=np? project. On the other hand, I hadn't really settled down on > >> what I think is the best way to approach the problem until the last > >> few years. But I would at least like to try to do something. > >> Jim Bromer > >> > >> > >> On Sun, Nov 8, 2015 at 5:16 PM, Steve Richfield > >> <[email protected]> wrote: > >> > Jim, > >> > > >> > You seem to be suffering from a malady that many others on this forum > >> > appear > >> > to be suffering from. The primary symptom is the belief that simple > >> > observation of HIGHLY noise-ridden text can lead machines to useful > >> > epiphanies. > >> > > >> > The problem is that pretty much everything people write is, in a word, > >> > wrong. Overbroad statements (and natural languages can NOT precisely > >> > bracket > >> > statements), statements made based on unstated presumptions (and no > one > >> > can > >> > list all their presumptions), statements made based on faulty models > >> > (and > >> > ALL models are faulty, as every physicist knows), confused meanings or > >> > words > >> > (most words have multiple meanings), lies made for economic or other > >> > gain, > >> > etc., etc., etc. It is difficult to find ANY clear statements that are > >> > unquestionably accurate in all of their potential meanings. > >> > > >> > OK, so suppose you accept the above and simply want to do the best you > >> > can. > >> > Still, you can NOT approach the capabilities of an average person, > >> > because > >> > we have a real world in which to test the many possible > interpretations > >> > of > >> > what we read, whereas a machine can only accept, reject, or assign a > >> > probability with NO other information. > >> > > >> > I used to believe as you do - until 2001 when I became very sick. It > >> > took me > >> > 3 months of every conscious minute to figure out what was wrong and > what > >> > might be done about it. Sure I got most of my information from books > or > >> > the > >> > Internet, but there remained several very different models in which > this > >> > all > >> > fit, which I resolved with phone calls to key researchers, and a > little > >> > of > >> > my own primary experimentation to sort the flyshit from the pepper. > >> > Still, I > >> > remained unsure until what should work did work to cure my condition. > >> > > >> > When I went back to figure out how the Internet might be reorganized > to > >> > reduce my search from 3 months to a few minutes, the structure of > >> > DrEliza > >> > emerged, and later my patent. > >> > > >> > The problem is that to usefully solve problems you need MODELS, yet > >> > natural > >> > language (and most human thinking) predates this concept and only > >> > provides > >> > INFORMATION. Sometimes you can construct a model from information, but > >> > this > >> > is RARE. Making models requires highly qualified geniuses who can get > >> > their > >> > arms around entire fields and synthesize models that fit ALL known > >> > observations. I have done this in several narrow areas, but it will > take > >> > a > >> > LOT more of this to transform the Internet to a model-based system > from > >> > which an AI/AGI can usefully address problems of all types. > >> > > >> > Further, natural language is highly granular - there are far more > things > >> > that you can NOT say than things you CAN say, so people without even > >> > thinking about it round to the nearest syntactically expressible > meaning > >> > in > >> > EVERYTHING they say or write. This "rounding" completely destroys any > >> > ability to construct accurate models. > >> > > >> > Some languages have weak workarounds to this, e.g. German with its > >> > concatenated words, or Arabic where they alter spellings for emphasis, > >> > but > >> > these measures only slightly reduce their granularity. > >> > > >> > All in all, each person here must either find a way to jump from > >> > information > >> > to models, or abandon this quest. Sure, information can help people > >> > solve a > >> > problems whose solution has already been stated, but there are already > >> > plenty of experts around who do this quite well. It is the UNsolved > >> > problems > >> > that are interesting, and it is these UNsolved problems that can NOT > >> > EVER be > >> > solved by automated means based on people's writings. > >> > > >> > How can I say not EVER when writings continue to accumulate? Because > >> > society's problems also continue to accumulate, so as people find > >> > solutions > >> > to past unsolved problems, even more new problems emerge to replace > >> > them. > >> > > >> > I hereby proclaim your apparent quest to be theoretically unachievable > >> > for > >> > the many reasons outlined above. Sure it would be of astronomical > value, > >> > like the methodology to change lead into gold that so many people put > so > >> > much effort into, but why waste your time unless/until you can find > SOME > >> > way > >> > around the above-listed barriers. > >> > > >> > Steve > >> > ===================== > >> > > >> > On Sun, Nov 8, 2015 at 9:00 AM, Jim Bromer <[email protected]> > wrote: > >> >> > >> >> Steve, > >> >> It will take me some time to reply carefully so let me respond to > >> >> something I feel strongly about. > >> >> > >> >> >>And because it is not an all encompassing > >> >> language of communication it could be used to test the 'emergence' of > >> >> insight that could arise if enough preparatory work had been done, > >> >> even if I haven't figured out how that could be done without the > >> >> artificial referent language. > >> >> >> > >> >> > >> >> >There is a VAST chasm between being able to define language > >> >> > constructions > >> >> > and meanings, and "insight". > >> >> > > >> >> > >> >> I believe there is a vast chasm between 'simple associations' or > >> >> 'simple > >> >> correlations' or associations derived from 'neural networks' and > >> >> conceptual > >> >> integration. Sophisticated artificial conceptual integration would > make > >> >> 'insight' feasible and simple examples across a wide range of subject > >> >> matter > >> >> should arise fairly quickly. But since AI programs are only capable > of > >> >> the > >> >> simplest examples of 'insight' then declarations about the chasm > >> >> between AI > >> >> and 'insight' are expected. So I totally disagree with you about > this. > >> >> I > >> >> feel that your feelings about this are historically accurate but have > >> >> little > >> >> to do with the potential near-future. As I say, I do not recall > hearing > >> >> about an AI program that is capable of learning via conversation > except > >> >> for > >> >> extremely simple domains. I feel that I have a solution for this > >> >> problem but > >> >> the trial and error process of getting from where I am now and where > I > >> >> think > >> >> I can get is so overwhelming a challenge that my decision to use the > >> >> artificial referent para-language makes a sense. > >> >> > >> >> Jim Bromer > >> >> > >> >> On Sun, Nov 8, 2015 at 11:19 AM, Steve Richfield > >> >> <[email protected]> wrote: > >> >>> > >> >>> Jim, > >> >>> > >> >>> FINALLY - SOMEONE who wants to discuss PRACTICAL implementations of > >> >>> TAI/TAGI. > >> >>> > >> >>> Continuing... > >> >>> On Sun, Nov 8, 2015 at 7:14 AM, Jim Bromer <[email protected]> > >> >>> wrote: > >> >>>> > >> >>>> After I wrote that message I realized that I had tried to start > >> >>>> discussions about an artificial language that could be used to > shape > >> >>>> a > >> >>>> general AI program before. Many of these discussions were side > >> >>>> tracked > >> >>>> when people started talking about Esperanto or about lambda > calculus > >> >>>> based artificial languages and stuff like that. That is not what I > am > >> >>>> thinking of. > >> >>> > >> >>> > >> >>> You mean, having syntax like: > >> >>> > >> >>> When that I write "xxxx" I mean "yyy". > >> >>> > >> >>> to define idioms, for more subtle things like: > >> >>> > >> >>> Consider that when I write "," I may mean ";". > >> >>> > >> >>> which expresses potential alternative interpretations of future > >> >>> writings? > >> >>>> > >> >>>> > >> >>>> The artificial language could be used with video or audio or other > >> >>>> kinds of IO environments, but I would use it along side of an > attempt > >> >>>> to get the AI program to learn to use a natural language. > >> >>> > >> >>> > >> >>> I did a VERY similar thing in a FORTRAN/ALGOL/BASIC compiler I once > >> >>> wrote > >> >>> for Remote Time-Sharing Corp. It started out as a very simplistic > >> >>> metacompiler, to which I fed it a description of a more capable > >> >>> metacompiler, in which language I fed it a description of an > >> >>> optimizing > >> >>> metacompiler. > >> >>> > >> >>> This could easily be done in a language like English, where a > >> >>> rule-driven > >> >>> system like I have been discussing here has rules whose function is > to > >> >>> introduce new rules. > >> >>> > >> >>>> > >> >>>> One of the > >> >>>> dreams of old AI was that if you started instructing the program to > >> >>>> learn using the artificialities of some kind of language it would > >> >>>> eventually have enough information for genuine learning to emerge. > >> >>> > >> >>> > >> >>> The think that seems to be the killer here is erroneous learning of > >> >>> various sorts. Superstitious learning is theoretical unavoidable. > Once > >> >>> you > >> >>> get something erroneous into such a system, it becomes > >> >>> difficult/impossible > >> >>> to get it out. A VERY simple demonstration comes in trying to use > >> >>> Dragon > >> >>> NaturallySpeaking's speech input to correct its errors in your > >> >>> dictation. As > >> >>> you would expect it makes errors in trying to correct the errors, > and > >> >>> this > >> >>> often compounds to overwhelm any hope of setting things right. > >> >>> > >> >>> Add to that not knowing exactly what a computer got wrong, or even > >> >>> being > >> >>> able to recognize that the computer got something wrong, and you can > >> >>> see how > >> >>> difficult/impossible it is to correct wrongly "learned" rules. > >> >>> > >> >>>> > >> >>>> This never really worked. Why not? Partly because computers were > not > >> >>>> powerful enough in the old days > >> >>> > >> >>> > >> >>> And still aren't - unless you use my patented LFU methodology. > >> >>> > >> >>>> > >> >>>> and, in my opinion, AI researchers had > >> >>>> not appreciated the necessity of sophisticated data integration > >> >>>> methods for some reason. (Old computer systems might one day be > shown > >> >>>> to have been potentially powerful enough to run some future program > >> >>>> but they were not powerful enough to entertain the trial and error > >> >>>> process that would have been required using experimental programs > of > >> >>>> the day. > >> >>> > >> >>> > >> >>> The advantage in LFU is about the same as the advantage of a modern > PC > >> >>> over an old vacuum tube clunker, so yes, they could have done a LOT > >> >>> more way > >> >>> back then. > >> >>> > >> >>> The "cycle time" of an IBM-709 computer was 12 microseconds, and > most > >> >>> instructions took two cycles - one to access and interpret the > >> >>> instruction, > >> >>> and one to access and operate on the operand. > >> >>> > >> >>>> > >> >>>> For example, with better conceptual integration methods a > >> >>>> future efficient AI program might be used on an old computer system > >> >>>> just to show that it could be run on it.) > >> >>> > >> >>> > >> >>> No, except for a few in the Computer Museum's display in Cupertino > >> >>> they > >> >>> have all been melted down for their scrap metal, and the Museum > won't > >> >>> turn > >> >>> them back on. > >> >>>> > >> >>>> > >> >>>> So the artificial referent language would not be a complete > language > >> >>>> (of communication) like Esperanto wants to be. And it would not be > a > >> >>>> logically sound language like lambda calculus wants to be. It could > >> >>>> be > >> >>>> used to establish referents from the IO data environment. It would > >> >>>> need to be capable of denoting a distinction between how those data > >> >>>> objects can be used. For example in natural language there is an > >> >>>> important distinction between syntax and semantics. So if I used > this > >> >>>> referent language with a natural language IO then one of the > >> >>>> artificialities would be to distinguish syntactic relations from > >> >>>> semantic relations. On the other hand, this distinction is not > always > >> >>>> necessary, desired or clear cut. To explain this, many (or maybe > >> >>>> most) > >> >>>> (what I think are) desirable syntactic relations are based on some > >> >>>> semantic conditions. But then again there is no reason not to > design > >> >>>> the artificial language to be able to represent relations that are > >> >>>> mixes of semantics and syntax. > >> >>> > >> >>> > >> >>> Leaving a stupid computer to untangle such messes is probably a > >> >>> mistake. > >> >>> However, it would be fairly easy to provide a mechanism for people > to > >> >>> specify such things. > >> >>>> > >> >>>> > >> >>>> As I see it, the main problem with language based AI has been the > >> >>>> lack > >> >>>> of a really good conceptual integration solution. > >> >>> > >> >>> > >> >>> This broad statement could be said about ANYTHING people haven't yet > >> >>> seen > >> >>> a way to make work - like AGI. > >> >>>> > >> >>>> > >> >>>> One of the reasons I write to groups like this is that I want to > get > >> >>>> some ideas about how an idea might work. > >> >>> > >> >>> > >> >>> Same here. > >> >>> > >> >>>> > >> >>>> But when I wrote about an > >> >>>> artificial para-language before I wasn't really sure it I even > wanted > >> >>>> to use it. I finally have come to the conclusion that it makes a > lot > >> >>>> of sense. I can use it to speed up tests about my AI/AGI theories > but > >> >>>> then I could also test those theories with more relaxed > instructions. > >> >>>> So the artificial para-referent language would not a all > encompassing > >> >>>> language of communication, it would not be a logically sound > language > >> >>>> other than to denote semantic and syntactic references and > relations > >> >>>> based on mixes of semantic and syntactic references. It could also > >> >>>> denote relations that I think would be important to a text-based > >> >>>> AI/AGI program. Because the logic of the method would not be tight > >> >>>> and > >> >>>> a contradicting case would not (always) lead to an artificially > >> >>>> reported error, the AI methods would have to do some learning for > >> >>>> itself. So the para-referent language would not sidetrack the whole > >> >>>> effort because if the AI methods have to have the potential to > >> >>>> exhibit > >> >>>> some genuine learning. And because it is not an all encompassing > >> >>>> language of communication it could be used to test the 'emergence' > of > >> >>>> insight that could arise if enough preparatory work had been done, > >> >>>> even if I haven't figured out how that could be done without the > >> >>>> artificial referent language. The benefit is that I could use it to > >> >>>> test and develop my AI theories. I am really excited by this idea > >> >>>> this > >> >>>> time. > >> >>> > >> >>> > >> >>> There is a VAST chasm between being able to define language > >> >>> constructions > >> >>> and meanings, and "insight". > >> >>> > >> >>> Steve > >> >>> ====================== > >> >>>> > >> >>>> Jim Bromer > >> >>>> > >> >>>> > >> >>>> On Sat, Nov 7, 2015 at 10:22 PM, Jim Bromer <[email protected]> > >> >>>> wrote: > >> >>>> > I was just working on my latest p=np? idea and I hit up against > >> >>>> > method > >> >>>> > that is either in np or is otherwise extremely inefficient. So I > >> >>>> > have > >> >>>> > to come to the conclusion that the human mind is not capable of > SAT > >> >>>> > in > >> >>>> > p. > >> >>>> > > >> >>>> > So then how do we figure how to deal with so many complicated > >> >>>> > situations? Of course I still don't know because so many > situations > >> >>>> > seem similar to a SAT problem. The mind must be able to detect > many > >> >>>> > different things that are going on at once or which might be > useful > >> >>>> > to > >> >>>> > recall from memory to deal with a situation. But still, there is > >> >>>> > nothing in my own introspective analysis of my thinking which > looks > >> >>>> > anything like a p=np process. > >> >>>> > > >> >>>> > So what is wrong with AI? One thing that AI has been consistently > >> >>>> > lacking is the ability to learn through conversation. My feeling > is > >> >>>> > that this is not just a problem with communication but a learning > >> >>>> > problem as well. In other words AI is not able to truly learn > >> >>>> > except > >> >>>> > in a few special cases. Most of those special cases are examples > of > >> >>>> > narrow AI but there are others where the learning that takes > place > >> >>>> > isn't necessarily like other narrow AI but where the domain of > >> >>>> > learning is so restricted that it is narrow in the sense that the > >> >>>> > applicability of the method is limited. > >> >>>> > > >> >>>> > Then I started thinking of an artificial language which can refer > >> >>>> > to > >> >>>> > situations or objects in the IO data environment and which can be > >> >>>> > used > >> >>>> > to instruct a program as it is running. I think this is an > unusual > >> >>>> > idea. > >> >>>> > > >> >>>> > One of the characteristics about programming methods that seem to > >> >>>> > catch on with programmers is that they can be used in a very > simple > >> >>>> > manner and in more complicated programming. I think an artificial > >> >>>> > language which could be used to instruct a computer to notice > >> >>>> > objects > >> >>>> > in the IO data environment and which could also be used to refine > >> >>>> > those instructions using this artificial language with the > >> >>>> > references > >> >>>> > that it had previously established has a lot of potential. And it > >> >>>> > can > >> >>>> > help us become more clear about what is needed to make better AGI > >> >>>> > programs. > >> >>>> > Jim Bromer > >> > >> > >> ------------------------------------------- > >> AGI > >> Archives: https://www.listbox.com/member/archive/303/=now > >> RSS Feed: > https://www.listbox.com/member/archive/rss/303/10443978-6f4c28ac > >> Modify Your Subscription: https://www.listbox.com/member/?&; > >> Powered by Listbox: http://www.listbox.com > > > > > > > > > > -- > > Full employment can be had with the stoke of a pen. Simply institute a > six > > hour workday. That will easily create enough new jobs to bring back full > > employment. > > > > AGI | Archives | Modify Your Subscription > > > ------------------------------------------- > AGI > Archives: https://www.listbox.com/member/archive/303/=now > RSS Feed: https://www.listbox.com/member/archive/rss/303/10443978-6f4c28ac > Modify Your Subscription: > https://www.listbox.com/member/?&; > Powered by Listbox: http://www.listbox.com > -- Full employment can be had with the stoke of a pen. Simply institute a six hour workday. That will easily create enough new jobs to bring back full employment. ------------------------------------------- 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
