collatz left/right contd

this idea occurred to me. as remarked some prior, there seems to be some pattern in a lot of trajectories in that its basically just an upslope and a downslope, eg within the glide region. how much of a pattern is this? or is it just highly related to all the glide generation algorithms devised so far? what would a trajectory that deviates from it look like?

this code splits the trajectory (glide only) into left and right upslope and downslope sides and then measures the mx value for each separately, trying to maximize it. the code has 3 modes: 1 maximizes left, 2 maximizes right, and 3 maximizes over both, but noticed the last one tends to settle on optimizing left after many iterations. the purple line is the mx value and the green line is the length of the “side” (upslope or downslope). another funky aspect of this code is that it seems to occasionally “paint itself into a corner” and fail to find increasing trends after long runs.

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warbotics 2016- Obama releases casualty figure, magic number 116

drone_takeoffhi all. now seems as good a time as any to write on this topic. the dallas killer robot taking out a sniper alarmingly blurs the line between military and civilian/ police use of robotics. but hey, thats always been what americans are good at right? we seem to have long had some pretty “mixed up boundaries” on use of (lethal) force esp compared/ contrast with other countries.

every few years there is a small outbreak or commotion over use of military drones. drones have probably killed a few thousand over the many years that theyve been used. by a massive sleight of hand the military classifies nearly all casualties as “enemy combatants” based on their proximity to the target. hey, tail wagging the dog right? that was an old brilliant satire movie from many years ago that nobody remembers anymore anyway.

anyway within last few weeks, obama officially finally released figures after many years of empty promises and footdragging and theres a smattering of headlines and editorials.[a]

the magic number is 116.

so now we can all just heave a massive sigh of relief, write it down on a yellow sticky note and put it on the refrigerator or whatever. 116 is not that bad. and obama can pat himself on the back for his amazing forebearance and (trying to get the right word here)… restraint. and oh yeah, that favorite military word, precision. oh lets face it whatever number he came up with, hed get all kinds of criticism on it right? clearly its a total no-win sitation for him. and hey, its not his problem in less than a ~½year anyway. whose the next commander in chief anyway? we can be sure either hillary or donald will do a better job, right?😮👿

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robotics 2016—dallas bomber, tesla autopilot, google reorg, etc

IFhi all, its a lot of very big news for robotics in 2016, this captures top developments, and this post is timed with the tesla crash that made huge headlines the last few weeks and is causing major/ intense spotlight-level scrutiny of tesla, musk, and automated driving capabilities in particular.[b]

have long predicted that there would be a 1st fatality due to auto driving tech and that day has now come to pass within the last few weeks. note the media is focused on one crash in particular but (my understanding) there were two separate crashes.

the other recent massive headline is the extraordinary improvised-on-spot use of a robot to deliver c4 explosive to “take out” a dallas sniper (using the sanitized/ near-euphemistic police language, essentially eerily the same as military terminology), causing some major headlines and controversy.[a] calling the robot a “bomber” seems like a strange new use of the english language, but probably the closest possible… the word “bomber” now referring to a non-human, semiautonomous entity/ machine but not an inanimate object either! science fiction meeting etymology/ everyday vernacular can be like that at times… headlines say “killer robot”… the picture is from [a9], a 2009 miami shot of a similar robot.

it would seem that the military use of robotics and civilian uses, up until now quite distinct, just got blurred to a frightening degree. but again this is mostly predictable. how long before terrorists mount plastic explosives on flying drones? am surprised ISIL has not already tried.

so we are getting a “rubber meets the road” scenario with robotics and its causing mass shockwaves. and am predicting this is only the beginning. with tesla, it sounded like an “accident waiting to happen” for those who track this kind of stuff. [b9] is esp informative/ relevant.

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summer fun/ trip: tech+art+cyber theme

hi all, switching it up with some personal summer news. got to go on a rare trip. hadnt been on a plane or beach in 6 yrs and am happy to break that “dry spell”. went to sandiego/ LA for a week. some tech angles on all that. as my young cohort/ prodigy/ “chip off the old block” says sometimes, it was “jampacked”

was struggling to try to come up with a unifying theme for this post and then thought about this angle. really enjoy the aesthetics of an area/ niche that might be called “tech art”. this is technology mixed with art/ entertainment. its crosscutting across different art forms.

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ML + AI advances 2016

hi all. machine learning + artificial intelligence are evolving very rapidly these days. very hard to keep up but heres a major effort to pound the latest headlines into a coherent summary. the media has picked up on the major horserace. a lot is being cast as corporations versus each other, mainly google[f], facebook[g], IBM, Apple, etc… with literally billions of dollars being thrown at it now, at this rate it looks like there is not a lot of question at this moment who is going to have the most cutting edge ML+AI in the near future, and hint, it isnt gonna be universities+academia. its being pitched as the next disruptive technology to hit silicon valley.

have some major qualms about this. there are only a few disruptive technologies per generation. ML+AI does seem to fit in this category but its much more inchoate than eg say web browsers, internet, email, or cell phones. even with good ML+AI its not so clear how to productize/ monetize it, and in a way Google is one of the only companies that has figured out how to do so, and its all based on a few basic concepts: relevant search and matching/ optimizing advertising buyers with ad space wrt ad auctions. and in a way, the relevant search algorithm only indirectly contributes to their bottom line. hearing about IBM putting millions of dollars into Watson research makes me wonder if theres definitely a light at the end of that tunnel. and whether its an oncoming train. etc

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