Sergio, In this and other postings, you are making the same mistake that most others in AGI make:
You point to the many areas where interesting things are obviously happening that people don't yet understand, and saying that THERE is where we should be working, not diagramming or simulating neurosystems, etc. It is not that you are "wrong", but rather that your view contains an oxymoron. What took a hundred million years of evolution and 200 different types of neurons to make work is NOT going to be "dreamed up" by anyone here or anywhere else. Maybe with another 1,000 years of talented mathematical work, there might be some light at the end of the tunnel. Obviously we don't want to wait that long, so we need to find another path. You are asking questions that are fundamentally mathematical in nature. These questions would have already been solved by talented mathematicians (there are lots of them), except that your observations are too vague to turn observations into problems, then into questions, and then into solutions. Any competent mathematician can answer a question. It takes a really good mathematician to transform a problem into a question. It is often beyond human capability to transform an observation into a problem. This has been and will continue to be the show stopper for AGI. Here, you either need an AGI to design an AGI, or you need more information than we now have. Having only my artificially enhanced intellect to apply, I am just pointing out the "obvious", at least obvious to me, that we need more information. Where would YOU look for more information? Once we have more information, it will take multidisciplinary cooperation that doesn't now exist to get over the remaining humps. More comments follow... On Sat, Jun 23, 2012 at 9:34 AM, Sergio Pissanetzky <[email protected]>wrote: > Alan, > > my point didn't get through. My only contribution to science is the > inference. I believe it is important, and I feel obligated to popularize > it. > To popularize, I need to talk applications, not just pure Math. > Without the math you aren't going anywhere. Of course that math doesn't now exist. Hence, I don't expect to see AGIs anytime soon, at least not until the AGI community gets onto a productive pathway. > > In NS, that means applications to the brain. I know a bunch of things about > the brain. They are things neuroscientists do not know. And I don't know > many of the things they do. In my mind, this calls for teamwork, not hide > in > a hole and shut up. > YES - it takes a combination of wet-lab science, math, and people like you who look at where this is all going, all working TOGETHER. > > Here are the things I know. I know the brain obeys laws of conservation, > just because it is a physical system, and I know that laws of conservation > are associated with symmetries in the physical system. I know the brain > makes invariant representations (the chair upside down is still a chair). I > would like to know if the two things are related. > Good observations and a start at formulating a problem. > > I see causality in the brain. Sensory organs collect causal information (it > is still causal even if rated pulses originate from a cone). Muscles are > driven by causal commands. Neurons firing cause other neurons to fire. > There > are exceptions, I know that too. > > Causal sets have symmetries, and they obey laws of conservation, which > result in invariant representations. I have collected some experimental > evidence suggesting that these representations are the same that the brain > makes, given the same information. Should I pursue these matters further? > Or > should I just ignore the whole thing because, for example , "neurons > sometimes fire at random?" How could a researcher distinguish "random" from "unknown function". When you see statements like this, just chalk it up to their ignorance. Note that there is good evidence that we compute, especially in our visual systems that have been most studied, with rates of changes to logarithms, and that logarithmic curves are discontinuous are zero. Hence, even the slightest of system noise around zero would be seen as apparently random pulses (from the ~10% of neurons that actually produce any pulses, as most neurons are continuously analog). Now, try to explain even this simple concept to a neuroscientist. They are most likely to inquire about what you have been smoking. Or because a cone on the retina gives out many > pulses instead of just one? > Maybe that is simply what is needed to work right? Understanding WHY that is needed to work right is a MUCH harder problem. > > The clue here is to pursue the big matters without getting bugged down in > the details. I think you are saying to look at things top-down rather than bottom-up, which I agree with. However, at some point the top and bottom must meet before you know enough to start coding. > I am trying to say something useful about the brain that > neuroscientists can understand, without sacrificing the big picture. I feel > free to disregard details when I believe that the big picture is > independent > of those details. For example, if a cone produces a string of pulses, not > just one as I proposed, would then the brain not be a physical system? > Would > it not obey conservation laws? Would it not make invariant representations? > If I can show that a chair upside down is a chair with one pulse, would > that > be necessarily false for 3 pulses? > Until you fully understand the problem that is being solved, you can't make ANY valid conclusions. You are now trying to think about this when the answers simply can't be reasoned out in the present lack of understanding of the PROBLEM. > > I know even more things that concern the brain. I know that EI is not an > algorithm, and can not be implemented as a circuit or network. I am very > concerned about projects to reverse-engineer the brain and simulate it on a > computer using a program. Because they are not even looking at the right > things. They can simulate the entire brain in ultimate detail, with strings > of pulses coming from cones, with all the details of the optical nerves, > and > still not find EI! So, how would you ever debug such a system? No, it is necessary to UNDERSTAND the vast majority what is happening to ever get a simulation to actually work. > Because it is not there. They ought to be looking at the > dynamics of the neurons, doing simple experiments with brain-on-a-dish or > retinas that compress, and trying to understand how it all works, before > embarking in blind efforts. > As in prior postings, this research is all funded by the Department of Health, and they don't give a damn about computation - just diseases. In short, I agree with you and point out that the fundamental underlying disagreement with the "world" is very political in nature. > > And so also should I. Try to apply EI to simple things, understand what > they > do, find the principle, and only then, with the principle in hand, embark > in > implementation details. > > The question is: do neurons do EI, or not? And if they do, how do they do > it? So how about some team work? > I have been trying to pull this together for decades, but STILL people just don't "get it". Neuro-scientists just don't see any value in math that they don't understand, Computer people can't see any value in understanding wetware when they see their programs working entirely differently, and the mathematicians hardly know where to start having not even been given "clean" observations, let alone problems or questions. This entire area is going nowhere until we get that teamwork you mentioned, and each of the three areas that need to come together sees the other two areas as being completely irrelevant. Given my past efforts and failures, I believe that we are bumping up against a fundamental limitation of the human brain - the inability to see the value of other views of things. This occurs in nearly every area of human endeavor, and especially here in AGI. It seems EVER so obvious to me that the crop of people here aren't going to be building any AGIs, because they are literally hiding from the very information they need to succeed. Steve ========================= > Sergio > > Some more: EI is behavior-preserving, there is no loss of information. EI > can be viewed as a function that maps from causets to structured causets. > The map is bijective. There exists an inverse function, which is > computable. > EI works by extracting entropy from a system, that's how it organizes the > system. The inverse function does the reverse, it disorganizes the system > by > adding entropy. > See Fig. 4 and text and reference in my Complexity paper for the question > about edges. EI does not actually find edges, it classifies the points into > categories, 3 in this case. To have edges, one would have to define what an > edge is. Try finding "edges" for the "areas" in the figure. There is more > than one way. > > > > > -----Original Message----- > From: Alan Grimes [mailto:[email protected]] > Sent: Friday, June 22, 2012 8:33 PM > To: AGI > Subject: Re: [agi] Prediction Did Not Work (except in narrow ai.) > > Sergio Pissanetzky wrote: > > Alan, > > > Alright. I thougth I answered 1 and 2 before, but here comes again. > > Take a retina. Light from whatever is outside illuminates the cones. > > Each cone generates an electric impulse. > > Wrong, a rate encoded (if I'm not mistaken) series of pulses that are > processed by the retinal ganglion cells. > > > That's the causal set. That's it: (light on cone ==> electrical > > impulse) times 100 million cones is the causal set. > > Prove it. > > Take an image and show how it can *REVERSIBLY* be encoded into a causal > set. > > If the transformation is not reversible then you are throwing away > information. --> FAIL. > > > And > > that's all the information you get. Look at it anyway you want, that's > > all the information you can get from the retina. Of course, each cone > > has a position in the body, > > Wrong. It has a receptive field. It is sensitive to light passing through a > cone, the tip of which is in the lense of the eye. The sum of the receptive > fields of all the cells in your eye is your visual field. > > It can be claimed that the entire nervous system is designed around the > visual sense. Because of the optical properties of the eye, the image on > your retina is upside down and backwards. Because there are more optic > nerves than somatic nerves, there is no "pyramidal tract" in the optic > nerve, it is a straight shot back to V1 which is upside down and backwards. > To keep everything consistent with the brain, the somatic nerves ARE > crossed > over the center line of the body and you find an upside down and backward > representation of your body on the post-central gyrus of your brain. So > yeah, your brain is upside down and backwards in your skull. > > > and the electric impulse came at a certain instant of time. > > To within about 1/15th-1/20th of a second or so depending on several > factors... > > > With hearing it is the same. Regarding "binaural", I do not disagree, > > I am only saying let's start with something simpler, monaural. If we > > can do it for a monaural causal set, we can also do it for a binaural > > one, but will have to buy an even bigger computer. > > Hearing, as is now commonly known, is processed in an organ called the > cochlea, it's a snail-shell shaped piece of bony anatomy that is embedded > in > the skull. I forget the exact mapping but it basically operates as a > spectrum analyzer for incoming frequencies. This system of the brain has > been reverse engineered to a large extent and there are some fairly > accurate > functional diagrams on the net. > > > "Reallistic" Well, sunlight and black > > dots is reallistic, you can look at black dots. For a more reallistic > > case, we will have to engineer the cones! (Yes, it's me saying engineer). > > Well there are a wide variety of cameras available. Furthermore, we know > that common video recordings, such as DVDs contain enough information for > visual perception, so therefore we have no reason to do anything with > regards to cone cells. > > > Surprisingly, however, we will NOT have to tell the causal set > > anything about the cones, so the engineering is external to EI, or to the > neurons. > > All that is needed is that "something" has caused the electric > > impulse. And then, we let EI or the brain to figure out what it was. > > Wrong. During embryonic development in some species, scientists have > detected patters of spontaneous activation across the retina. The > hypothesis > is that these "test patterns" pattern the cortex of the occipital lobe so > that an accurate spatial map is established. You continue to deny this fact > without explaining how your theory handles spatial information. > > > Burden of proof? That's unreallistic. Who do you think I am, Qicken > Loans? > > EI touches a variety of disciplines. AGI is just one of them. I have > > communication with people from several other disciplines. Should I > > become an expert in each one of them? My contribution to science is to > > have proved that EI exists and to have characterized it, and that's > > why I keep insisting about the section on Small Systems in my > > Complexity paper. Now, experts from the disciplines must take over. My > > part: continue developing the theory (it is not finished, not even > > close) and try to attract help from experts by popularizing my finding. > > You're jumping the gun. > > I'm not satisfied that you are continuing to think critically about your > idea. Instead, I see you promote it as a solution to problems in fields you > have not studied, even as an amateur. > > > Regarding 2, I thought I did that too. I showed useful results for the > > GUAPs in Computer Science, recognition of edges in vision, and > > Physics. That's only an enticement. > > Splendid! Where's the paper? I may have forgotten reading it already... > > > Sorry I am pissing you off so much about Neuroscience. I declare > > emphatically my knowledge on that to be very limited. But I can draw > > conclusions that may, repeat, may be useful to Neuroscience, and > > that's all I am trying to do. > > NO GOOD. I'm still a 2nd rate ignoramus when it comes to neural science but > I still know the essentials. If you can't be bothered to study, then STFU. > > > I have also insisted that the brain is the only known intelligent > > system, and that we have a lot to learn from it. But I've also said, > > the "lot" does NOT include the implementation of the brain. All we > > need is to understand the principles, and then we can start using the > > principles in new and creative ways, such as an artificial system, > > without ever having to simulate the brain in all its complexity. Sorry > > if you don't like this, but this is a cornerstone for me. > > Agreed. > > > For the sake of principles, I don't need to know very much about the > > 200 types of neurons. That doesn't mean I disdain that vast knowledge. > > Quite on the contrary. All I am saying is that, for now, it is not > > needed. Once the principle is set, then, not now, then it will be the > > right time to start examining neurological knowledge. By you, not me. > I'll > help all I can. > > People work in teams in Science, you know. > > But there are many principles. There are many anatomically and functionally > distinct neural circuits in the brain. The differences between cortical > regions is relatively minor but there are many other regions in the brain > with a great deal more diversity in structure and function. > > -- > E T F > N H E > D E D > > Powers are not rights. > > > > > > ------------------------------------------- > AGI > Archives: https://www.listbox.com/member/archive/303/=now > RSS Feed: https://www.listbox.com/member/archive/rss/303/18883996-f0d58d57 > Modify Your Subscription: > https://www.listbox.com/member/?&; > d2 > 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/303/10443978-6f4c28ac > 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-c97d2393 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-2484a968 Powered by Listbox: http://www.listbox.com
