hi all, ~250 links for 2nd half of 2018 AI + ML trends. very broad! AI/ML is now understood to be penetrating many fields/ areas. there are major (new) international govt initiatives, a new one announced in France by Macron.[c23]
this year looks a little more incremental than last year when Deepmind announced the Go game advancement. close to my own interests there is a lot of continued research into more advanced games such as starcraft and dota.[a4] there is bigger alignment with robotics.[a5] there are regular/ frequent announcements of major shifts/ innovations in methods of increasing sophistication/ scope.[a6]
closely tied into ethics analysis (covered heavily last blog) there is more serious/ heightened prognostication/ consternation of the future implications.[b] the tools/ chips hardware are advancing noticeably.[d][d2] there is top competition for/ jockeying among leaders in the field.[f] the sophia robot made a lot of headlines earlier in the year “for better or worse”.[i]
as noted in prior blog it looks to me like AI/ ML is in a sensitive/ vulnerable/ difficult/ at times awkward transition period of inching closer to AGI capabilities.
hi all. 2nd half AI in 2017 was very fast paced and as usual its hard to keep up. many headlines on the subj. this is a 2nd half review.
seems like some of the biggest news is the increasing dominance of China in the area after the govt announced major initiatives, funding, and resolve/ determination.[b]
google/ deepmind continues to dominate headlines.[a] the other big news is googles alphago and alphazero that no longer required human training games![a2] officially its under the name of “reinforcement learning” but my feeling is that this technology is something like “directed learning” where the AI is manipulating its environment to “detect/ seek/ digest novelty,” and that this will be a key, paradigm shifting trend in the near future. the same algorithm also works in chess/ go!
starcraft[a3] and Dota are starting to show up in AI engines/ research and OpenAI just announced breakthru championship level play vs humans in Dota, and Deepmind is attacking starcraft. despite all this major domination, it looks like games will not move out of cutting edge research anytime soon.[c4]
another notable shift/ trend is that AI/ machine learning is starting to couple stronger with physics and robotics. eg Deepmind humanoid walking simulations etc.
hi all. blade runner 2049 came out a few mos ago, liked it a lot. it did medium business at the box office worldwide and was something of a domestic underperformer. hey, the 1st one was too right?
am a neon collector and got some of the idea from this movie. isnt it neat that neon has a nearly 1-century long history at this point, and showed up in a big way in a scifi movie. a motif for the future.
one of the highlights for me of the new movie was the las vegas exterior desert scenes. amazing! mesmerizing!
another big highlight for me was the virtual gf character “joi” played by ana de armas. it was said in 1 of the original reviews that “the cyborgs/ replicants are more human than the human characters.” was thinking that about joi. it seemed she had more empathy/ emotional intelligence than anyone else in the movie.
so here is maybe some small )( discrepancy between geek taste and mass cultural taste. think lots of the movie was geek nirvana.
theres a scene where the blade runner buys a emanator instead of a emulator (the latter of which is a decades old real software engr technology). just a few letters make all the difference. the emanator gives joi a 3d body. sort of like dynamic 3d printing? seems completely physically impossible but thankfully that never stopped a great scifi concept.
hi all. kurzweil wrote in 2006 “the singularity is near”. foreboding words! but today, still maybe more of a feeling than a fact. definitely, the AI field has started to mature into a new steady advance period/ era in the last few years, also with a burst of energy/ enthusiasm/ innovation heralded by the Google Deepmind acquisition in 2014, and other massive shifts toward increased investment by large corporations and govts. the Musk Open AI initiative was announced in 2015.
the other massive milestone is the ready conquering of Go by Google in 2016 by AlphaGo. in late 2017, a new version AlphaZero was announced that plays superior to AlphaGo (at “beyond human grandmaster level”) after learning merely from the rules and reinforcement learning, ie no example human-level play presented as training whatsoever. AlphaZero also plays grandmaster level chess after learning “from scratch”. this breakthrough is not fully/ widely appreciated in some ways. it is the first case of a potentially more general algorithm for AI emerging from “previously relatively narrow” study of AI in games.
AI has the terminology “weak AI” and “strong AI” for different levels/ sophistication/ “ability”. more recently the term AGI, Artificial General Intelligence has been coined.
hi all. AI technology is really exploding in the last few years. the last big post/ compilation on the subj here was ~½ year ago and the links piled up in a blur since then. the main trigger for this post: the game of poker now seems to have “folded” to computer supremacy. a new paper was published on Deepstack and its highly competitive play, and Libratus is $800K up in a recent match against top experts (top players). my understanding is that there is still some weakness in multiplayer games and that the new breakthru is for 1-1 games, human vs computer, but presumably that razor-thin human edge might also melt away quickly.[a]
poker was a very good game for humans wrt our inherent/ evolved psychology. we (top humans that is) seem to have an intuitive grasp of how to bet based on the strength of cards, including the use of bluffing. it took computers until the 21st century to master this stuff. but it looks like they just passed the threshhold again. in a small surprise, it wasnt done by Deepmind but which is behind many other near-monthly, even verging on weekly breakthroughs.[c]
maybe not by total coincidence, the winning Libratus algorithm involves training a neural network to accurately estimate the search tree, quite similar to the Deepmind Go strategy that made huge headlines just a year ago. the media hasnt picked up on the poker competition as much as it did with Go… is it because cautious/ publicity shy academics have less PR instinct than google? or less budget? but maybe that “relatively low profile” will change in the weeks/ months ahead. hopefully there will be a very high profile contest that again captures widespread public interest/ imagination.
it seems the top poker competitions are typically held in Las Vegas afaik… what would it take to get the computers in that? wouldnt be cool if say Vegas (or some other high profile gambling center) decided to publicize it to attract attn/ tourism? but would the computer algorithms be competitive in the top multiplayer games? there have been increasing/ huge audiences for poker over last few years, not sure what all the factors are in in this surge (internet gambling might play a role…)
its neat to see academia still at the top of competitive research in AI. but that seems to be thinning somewhat over last few years as the massive corporations Google[b], Microsoft, Apple,[g] Facebook, Intel [f] and misc other corps [e] are snapping up AI talent like its a feverish arms race, and to some degree it is. theres also very fast/ dynamic startup/ other merger activity going on, and new research laboratories being founded.[h]