You can learn about the science of ridiculously complicated neural networks through a free Udacity course from Google,
https://www.udacity.com/course/deep-learning--ud730 it won't explain alphago's networks but will explain the general architecture (watts towers?) and the google Tensor Flow toolkit. I ended up skipping the exercises because of tool problems, but the video lectures give a pretty good overview of how to build inscrutable computer programs for several different classes of inscrutability. The discussion of how to feed images into deep learning networks probably covers a lot of the techniques used in alphago. -- rec -- On Mon, Mar 14, 2016 at 6:52 PM, Russ Abbott <[email protected]> wrote: > You can get most articles through Sci-Hub > <https://plus.google.com/u/0/+RussAbbott1/posts/5YGik2SsyDV>. The Nature > piece is available here > <http://sci-hub.io/http://www.nature.com/nature/journal/v529/n7587/full/nature16961.html>. > Amazing! > > -- Russ > > On Mon, Mar 14, 2016 at 3:38 PM Robert J. Cordingley < > [email protected]> wrote: > >> Access, for a fee, to the original Jan, 2016 Nature article on AlpahGo is >> at http://www.nature.com/nature/journal/v529/n7587/full/nature16961.html. >> The freely available abstract says it uses deep neural networks ('value >> networks' and 'policy networks'), tree search and Monte Carlo algorithms. >> Figures and tables with more information are also freely available from >> http://www.nature.com/nature/journal/v529/n7587/fig_tab/nature16961_ft.html >> >> Robert C >> >> >> On 3/13/16 8:53 PM, Steve Smith wrote: >> >> Me, I'm still stuck in the 80's... most of what I know about GO programs >> involves trying to solve them using cellular automata systems based on the >> promise of hardware implementations and other esoteric ways of doing CA >> computation... Tomasso Toffolli's custom CA hardware was one promising >> thing that I think eventually fizzled as was our own Jim Crutchfield's >> analog "video feedback" CA computing concepts... >> >> My own favorite which I went on to do some exploratory work in was the >> "memoisation" work of Bill Gosper which involves generating hash tables at >> each scale (say 3x3, 6x6, 12x12, 24x24) cell arrays such that if >> "redundant" patterns occurred at any scale they could be "looked up" >> instead of computed. In a 3x3 (9 cell) array, there are naturally only >> 512 (2^9) hash indices so the computation at that level is manageable by >> memoisation... while a 6x6 is 2^36 or roughly 64M entries, not quite so >> tractable/trivial if the distribution of possible configurations of binary >> CA were uniform... which interesting GO configurations naturally are >> NOT. A slight modification to this is that a binary CA is not sufficient >> since the states of each cell can be White/Black/Empty... so the math >> changes to 4^9 and 4^26,etc... >> >> Similar attempts were made for checkers and chess which as I remember, >> the state space for Checkers is much larger than for Chess (surprising?) >> but GO... much higher (larger board!) and the depth (number of relevant >> moves ahead) also much higher! >> >> I look forward to hearing what the current state of computer GO play >> might look like as well! >> >> - Steve >> >> >> There were stories during the expert systems episode in the 80's that >> some experts when debriefed in an attempt to identify their rules went on >> to lose faith in their own expertise and to resign from the field. Other >> anecdotes talked about how some experts weren't capable of expressing their >> expertise - such knowledge, skills & experience was referred to as >> 'compiled knowledge', accessible but not expressible, much like Artificial >> Neural Networks are. Work >> <http://www.sciencedirect.com/science/article/pii/0950705196819204> to >> address this problem has been underway since the 90's. Perhaps others here >> can provide an update? >> >> Robert C >> >> On 3/13/16 8:45 AM, Marcus Daniels wrote: >> >> I think a deep neural network trained from self play has a subjective, and >> even inscrutable inner representation. Imagine such techniques were applied >> to public policy decisions or medical diagnosis. Without a linguistic >> component that co-evolved to describe a taken action, one could be left with >> robot savants that outperformed humans on crucial tasks and no one, >> including the robot, would have any idea why. >> >> Sent from my iPhone >> >> >> On Mar 13, 2016, at 8:01 AM, Roger Critchlow <[email protected]> <[email protected]> >> wrote: >> >> I've been watching parts of the match between Lee Sedol and Alpha Go on the >> youtube deepmind channel. It's quite good, they start off with a discussion >> of the previous game, give running commentary during the game, and audibly >> gasp when the progress of the game shocks them. The post match press >> conferences are not to be missed, either. It's a completely trump free zone. >> >> But you're looking at a full day's work for each game, 6 hours and 17 >> minutes of video from last night's game which Lee Sedol won. I was too >> tired to stay up and watch so I tuned into youtube this morning and watched >> the endgame. >> >> Apparently I forwarded past the key move, #78, which a Chinese journalist, >> quoting a Chinese commentator, called "a God's move". Lee Sedol replied >> that it was the only move he had at the time, that he had thought it would >> be easier to make some profit, but it was quite difficult. >> >> So the same play is described as both creative genius and inevitable in the >> space of a few sentences. Glad to know that some things will never change. >> >> -- rec -- >> >> >> ============================================================ >> FRIAM Applied Complexity Group listserv >> Meets Fridays 9a-11:30 at cafe at St. John's College >> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com >> >> ============================================================ >> FRIAM Applied Complexity Group listserv >> Meets Fridays 9a-11:30 at cafe at St. John's College >> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com >> >> >> -- >> Cirrillian >> Web Design & Development >> Santa Fe, NMhttp://cirrillian.com281-989-6272 (cell) >> Member Design Corps of Santa Fe >> >> >> >> ============================================================ >> FRIAM Applied Complexity Group listserv >> Meets Fridays 9a-11:30 at cafe at St. John's College >> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com >> >> >> >> >> ============================================================ >> FRIAM Applied Complexity Group listserv >> Meets Fridays 9a-11:30 at cafe at St. John's College >> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com >> >> >> -- >> Cirrillian >> Web Design & Development >> Santa Fe, NMhttp://cirrillian.com281-989-6272 (cell) >> Member Design Corps of Santa Fe >> >> ============================================================ >> FRIAM Applied Complexity Group listserv >> Meets Fridays 9a-11:30 at cafe at St. John's College >> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com > > > ============================================================ > FRIAM Applied Complexity Group listserv > Meets Fridays 9a-11:30 at cafe at St. John's College > to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com >
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