{"id":207931,"date":"2017-02-14T10:36:10","date_gmt":"2017-02-14T15:36:10","guid":{"rendered":"http:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/uncategorized\/ais-factions-get-feisty-but-really-theyre-all-on-the-same-team-wired.php"},"modified":"2022-08-01T07:11:14","modified_gmt":"2022-08-01T11:11:14","slug":"ais-factions-get-feisty-but-really-theyre-all-on-the-same-team-wired","status":"publish","type":"post","link":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/artificial-intelligence\/ais-factions-get-feisty-but-really-theyre-all-on-the-same-team-wired.php","title":{"rendered":"AI&#8217;s Factions Get Feisty. But Really, They&#8217;re All on the Same Team &#8211; WIRED"},"content":{"rendered":"<p><p>          Slide:          1 \/          of 1. Caption: Getty Images        <\/p>\n<p>    Artificial intelligence is not one thing, but many, spanning    several schools of thought. In his book The Master    Algorithm, Pedro Domingos calls them the tribes of AI.  <\/p>\n<p>    As the University of Washington computer scientist explains,    each tribe fashions what would seem to be very different    technology. Evolutionists, for example, believe they can build    AI by recreating natural selection in the digital realm.    Symbolists spend their time coding specific knowledge into    machines, one rule at a time.  <\/p>\n<p>    Right now, the connectionists get all the press. They nurtured    the rise of deep neural networks, the pattern    recognition systems reinventing the likes of Google, Facebook,    and Microsoft. But whatever the press says, the other tribes    will play their own role in the rise of AI.  <\/p>\n<p>    Take Ben Vigoda, the CEO and founder of Gamalon. Hesa    Bayesian, part of the tribe that believes    in creating AI through the scientific method. Rather than    building neural networks that analyze data and reach    conclusions on their own, he and his team useprobabilistic programming, a technique in    which they start with their own hypotheses and then use data to    refine them. His startup, backed by Darpa, emerged from stealth    mode this morning.  <\/p>\n<p>    Gamalons tech can translate from one language to another, and    the company isdevelopingtools that businesses can    use to extract meaning from raw streams of text. Vigoda claims    his particular breed of probabilistic programming can produce    AI that learns more quickly than neural networks, using much    smaller amounts of data. You can be very careful about what    you teach it, he says, and can edit what youve taught it.  <\/p>\n<p>    As others point out, an approach along these lines is essential    to the rise of machines capable of truly thinking like humans.    Neural networks require enormous amounts of carefully labelled    data, and this isnt always available. Vigoda even goes so    far as to say that his techniques will replace neural networks    completely, in all applications. That is very, very clear, he    says.  <\/p>\n<p>    But just as deep learning isnt the only way to artificial    intelligence, neither is probabilistic programming. Or Gaussian processes. Or evolutionary computation. Or reinforcement learning.  <\/p>\n<p>    Sometimes, the AI tribesbadmouth each other. Sometimes, they play    up their technology at the expense of the others. But the    reality is that AI will risefrom many technologies    working together. Despite the competition, everyone is working    toward the same goal.  <\/p>\n<p>    Probabilistic programming lets researchers build machine    learning algorithms more like coders build computer programs.    But the real power of the technique lies inits ability to    deal with uncertainty. This can allow AI to learn from less    data, but it can also helpresearchers understand why an    AI reaches particular decisionsand more easily tweak the AI if    they dont agree with those decisions. True AI will need all    that, whether it powers a chatbot trying to carry on a    human-like conversation or an autonomous car trying to avoid an    accident.  <\/p>\n<p>    But neural networks have proven their worth with, among other    things, image and speech recognition, and theyre not    necessarily in competition with techniques like probabilistic    programming. In fact, Google researchers are building systems    that combine the two. Their strengths complement one another.    Deep neural networks and probabilistic models are closely    related, says David Blei, a Columbia University computer    scientist and an advisor to Gamalon who has worked with Google    research on these types of mixed models. Theres a lot of    probabilistic modeling happening inside neural    networks.  <\/p>\n<p>    Inevitably, the best AI will combine several technologies. Take    AlphaGo, the breakthrough system built by Googles DeepMind    lab. It combined neural networks with reinforcement learning and other    techniques. Blei, for one, doesnt see a world oftribes.    It doesnt exist for me, he says. He sees a world in which    everyone is reaching for the same master algorithm.  <\/p>\n<p><!-- Auto Generated --><\/p>\n<p>Here is the original post:<\/p>\n<p><a target=\"_blank\" rel=\"nofollow noopener\" href=\"https:\/\/www.wired.com\/2017\/02\/ais-factions-get-feisty-really-theyre-team\/\" title=\"AI's Factions Get Feisty. But Really, They're All on the Same Team - WIRED\">AI's Factions Get Feisty. But Really, They're All on the Same Team - WIRED<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p> Slide: 1 \/ of 1. Caption: Getty Images Artificial intelligence is not one thing, but many, spanning several schools of thought. In his book The Master Algorithm, Pedro Domingos calls them the tribes of AI.  <a href=\"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/artificial-intelligence\/ais-factions-get-feisty-but-really-theyre-all-on-the-same-team-wired.php\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"limit_modified_date":"","last_modified_date":"","_lmt_disableupdate":"","_lmt_disable":"","footnotes":""},"categories":[13],"tags":[],"class_list":["post-207931","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence"],"modified_by":"Danzig","_links":{"self":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts\/207931"}],"collection":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/comments?post=207931"}],"version-history":[{"count":0,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts\/207931\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/media?parent=207931"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/categories?post=207931"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/tags?post=207931"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}