Colin, will your proposed paper contain an experimental results section? I realize you favor the neuroscience approach to AGI. We need neuroscience to figure out how the brain does what it does, as well as computer science to test the theories that it suggests. Have you done any experiments on human or animal brains?
I'm not interested in yet another untested design or proposal for AGI. I wrote one in 2008. I'm not going to build it because it will cost USD $1 quadrillion. http://mattmahoney.net/agi2.html Nor am I interested in theories about consciousness. We will spend $1 quadrillion globally on human labor over the next 12 years doing work that machines aren't smart enough to do. To solve this problem, we need machines that can see, hear, navigate, understand language, evaluate art, model human behavior, and do everything else that people can do. But there is no need to simulate human weaknesses like emotions or poor memory in order for it to pass the Turing test. I don't care if you think it thinks or not, any more than Turing cared. I am not interested in economic or social theories on what will happen when machines put us all out of work. The more we automate, the more the cost of labor rises. Do you understand why? I am interested in actual experimental results that further goals toward AGI. My results, if you care to include them: First: A 13 year long evaluation of over 1000 versions of 200 text compression algorithms. http://mattmahoney.net/dc/rationale.html My conclusions are: 1. The best language models are based on neural networks (which we now know is true for vision and robotics as well). 2. Intelligence (measured by prediction accuracy) increases with the log of computing speed and the log of memory. Second: my cost estimate for AGI: http://mattmahoney.net/costofai.pdf The cost is based on the computing power of the human brain (1 to 10 petaflops, 0.1 to 1 petabyte) times 7 billion people, collecting 10^17 bits of global human knowledge not yet on the internet at $0.01 per bit, and the complexity of our DNA, equivalent to 300M lines of code. If you want to prevent another AI winter, then solve the power problem. A petaflop computer uses 1 MW of electricity. 7 billion of these would use 7000 TW. Global energy production is 15 TW. You can't reduce power consumption by making transistors smaller because you can't make transistors smaller than atoms. If you want to get anywhere close to the Landauer limit of 3 x 10^-21 J per bit operation, then you need to compute by moving atoms instead of electrons, like our cells and our brains do at a global cost of 0.7 TW. On Thu, Jun 27, 2019 at 10:56 PM Colin Hales <col.ha...@gmail.com> wrote: > > On Fri, Jun 28, 2019 at 10:33 AM Steve Richfield <steve.richfi...@gmail.com> > wrote: >> >> Colin, >> >> The obvious thing missing from neuroscience and AGI is application of the >> Scientific Method. >> >> Theory: give enough computer scientists enough keyboards and time, and they >> will eventually figure out or stumble on whatever it takes to have general >> intelligence >> >> Experiment: let the world's programmers work on this for half a century. >> >> Results: Zero, nada, nothing. Experiment failed. Time for another theory. >> >> My/Our? Theory: Use math to predict what might work to do the needed >> processing, physics to evaluate whether biological neurons might be capable >> of such things, neuroscience to see if these actually occur in biology, >> computer science (AGI) to simulate large systems of identified components, >> etc. >> >> To illustrate, we have argued in the past whether the Hall effect is >> significantly responsible for mutual inhibition. This micro-dispute can only >> exist in our current broken "system", because once a new integrated field >> has emerged, some bright physicist would spend a week running numbers >> through the equations to provide a definitive answer that we would both >> accept. >> >> What we seem to need here is some sort of "constitution" for people to >> digitally sign onto. I thoroughly expect a coming AGI disaster much like the >> Perceptron Winter. Maybe if we point the way to the future via competent >> research BEFORE the crash, we can preserve future research while these folks >> join the ranks of the homeless. >> >> Let's wring out any differences we might have and put this together. >> >> Thoughts? >> >> Steve > > > Yes. Let's. There is a lot to sort out. > > I have just embarked on writing a paper to sort this out once and for all. > It's my last attempt to get this very issue sorted out. The writing will > benefit from a serious pile of adversarial collaboration from yourself and > others. Ben? You interested? > > I have one and only one perspective on the issue that I have not tried. Maybe > it will push it over the line. I have written this cross-disciplinary thing > out from so many disciplinary perspectives I have lost count. All shot > blanks. And a sorry story it is. I have 1 approach left. Before that, this is > my personal position and preferred way to handle it if it happens in this > place: > > 1) I have taken the IP warrior hat off, and all my ideas will be in the > paper, including the chip design concept. 100% ownership of something that > goes nowhere = ...let me do the math ... hmmm. $Bugger-all in any currency. > 2) Co-authors. This must be a collaboration with at least 3 authors. I have > some ideas for prospective people. Anyone that can make a viable textual > contribution that makes it into the final version gets authorship. Explicit > acknowledgement will cover everything else. It would be very cool to be able > to put the names of a couple of hundred people in the acknowledgements. > 3) The text shall be fed to the commentariat in an ARXIV context for serious > adversarial critique prior to submission in any journal. > 4) The paper shall be of the ilk (scholastic standard) of those that caused > the trajectory of the state of AGI art to go the way it has e.g. Turing, Von > -Neumann... and e.g. my fave, probably the most influential (required > reading!) : Pylyshyn, Z.W. (1980). Computation and cognition: Issues in the > foundations of cognitive science. Behavioral and Brain Sciences 3, 111-132. > https://www.southampton.ac.uk/~harnad/Temp/.pylyshynBBS.pdf > 5) It shall be published in a journal with suitable impact. > > I already know what the outcome is in terms of its changes to the science of > AGI. I have already prepared the question leading to it in the final chapter > of my book. But that's all moot. Let's re-discover it in the paper's own > narrative. Shoot it to death if you can. Put me out of my misery! > > It's kind of weird that such a paper would be produced somewhat under the > gaze of an AGI forum. But I'm OK with that if you are. We can manage that > aspect offline a bit, if needed. It would be good if we can carry the whole > forum along with us to its conclusion. If we can do that, surely it counts > for something? Personally I think it apt that a serious left turn in AGI > science should come from a place like this, and a social media community of > this kind, where stakeholders abound. It would be very cool to be able to > tell any potential reviewers to join the forum to read the archives covering > the creation of the work! > > If the social media side gets too hard to manage we can bail and go off line. > BTW you can bail any time. I'll be doing this anyway, one way or another. > Just tell me to EFF OFF and I will. :-) > > Comments? ... Good to go? Or not? > > Colin > > Artificial General Intelligence List / AGI / see discussions + participants + > delivery options Permalink -- -- Matt Mahoney, mattmahone...@gmail.com ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T87761d322a3126b1-M39cfdbdd305169afd98f95a9 Delivery options: https://agi.topicbox.com/groups/agi/subscription
