{"id":337389,"date":"2017-04-02T05:29:37","date_gmt":"2017-04-01T21:29:37","guid":{"rendered":"http:\/\/techcrunch.com\/?p=1471799"},"modified":"2017-04-02T05:29:37","modified_gmt":"2017-04-01T21:29:37","slug":"discussing-the-limits-of-artificial-intelligence","status":"publish","type":"post","link":"https:\/\/people.utm.my\/asmawisham\/discussing-the-limits-of-artificial-intelligence\/","title":{"rendered":"Discussing the limits of artificial intelligence"},"content":{"rendered":"<div class=\"byline contributor-byline\" readability=\"5.5970588235294\">\n<div class=\"name\" readability=\"7\">\n<p><span class=\"name-container\">Alice Lloyd George<\/span> <span>Contributor<\/span><\/p>\n<\/p><\/div>\n<p class=\"bio\"><a href=\"http:\/\/www.rre.com\/alice-lloyd-george\/\">Alice Lloyd George<\/a> is an investor at <a href=\"http:\/\/www.rre.com\/\">RRE Ventures<\/a> and the host of <a href=\"http:\/\/theflux.libsyn.com\/podcast\">Flux<\/a>, a series of podcast conversations with leaders in frontier technology.<\/p>\n<div class=\"more-posts\" readability=\"6.3614457831325\">More posts by this contributor:\n<\/div>\n<\/div>\n<p><span class=\"c4\">It\u2019s hard to visit a tech site these days without seeing a headline about deep learning for X, and that AI is on the verge of solving all our problems. <a target=\"_blank\" href=\"http:\/\/www.psych.nyu.edu\/gary\/\">Gary Marcus<\/a> remains skeptical.<\/span><\/p>\n<p><span class=\"c4\">Marcus, a best-selling author, entrepreneur, and professor of psychology at NYU, has spent decades studying how children learn and believes that throwing more data at problems won\u2019t necessarily lead to progress in areas such as understanding language, not to speak of getting us to AGI \u2013 artificial general intelligence.<\/span><\/p>\n<p>Marcus\u00a0is the voice of anti-hype at a time when AI is all the hype, and in\u00a02015 he translated his thinking into a startup,\u00a0Geometric Intelligence, which\u00a0uses insights from cognitive psychology to build\u00a0better performing, less data-hungry\u00a0machine learning systems. The team was acquired by Uber in December to\u00a0run Uber\u2019s AI labs, where his cofounder\u00a0<a target=\"_blank\" href=\"https:\/\/newsroom.uber.com\/announcing-zoubin-ghahramani-as-ubers-chief-scientist\/\">Zoubin Ghahramani\u00a0has now been appointed\u00a0chief scientist.<\/a>\u00a0So what did the tech giant see that was so important?<\/p>\n<p><a target=\"_blank\" href=\"https:\/\/itunes.apple.com\/us\/podcast\/flux\/id1192848099?mt=2#episodeGuid=1e5bfc052e8f18ae72dad1c6ab9a36b4&#038;at=11lDJ&#038;ct=23232bca868b65555e3b9b375a2dde0d\">In an interview for Flux<\/a>,\u00a0I sat down with Marcus, who<span class=\"c4\">\u00a0discussed why\u00a0deep learning is\u00a0the hammer that\u2019s making all problems look like a nail<\/span>\u00a0and why his alternative sparse data approach is so valuable.<\/p>\n<p>We also got into\u00a0the challenges of being an AI\u00a0startup competing with the\u00a0resources of Google,\u00a0how corporates aren\u2019t focused on what society actually needs from AI,\u00a0his proposal to revamp the outdated\u00a0Turing test with a\u00a0multi-disciplinary\u00a0AI triathlon, and why programming a robot to understand \u201charm\u201d is so difficult.<\/p>\n<p><span class=\"embed-youtube c6\"><iframe loading=\"lazy\" class=\"youtube-player c5\" type=\"text\/html\" width=\"640\" height=\"390\" src=\"https:\/\/www.youtube.com\/embed\/IBoJcDlqmo0?version=3&#038;rel=1&#038;fs=1&#038;autohide=2&#038;showsearch=0&#038;showinfo=1&#038;iv_load_policy=1&#038;wmode=transparent\" allowfullscreen=\"true\">[embedded content]<\/iframe><\/span><\/p>\n<p class=\"m_4570964794744971347gmail-graf m_4570964794744971347gmail-graf--p\"><strong class=\"m_4570964794744971347gmail-markup--strong m_4570964794744971347gmail-markup--p-strong\">Gary you are well known as a critic of this technique, you\u2019ve said that it\u2019s over-hyped. That there\u2019s low hanging fruit that deep learning\u2019s good at\u200a\u2014\u200aspecific narrow tasks like perception and categorization, and maybe beating humans at chess, but you felt that this deep learning mania was taking the field of AI in the wrong direction, that we\u2019re not making progress on cognition and strong AI. Or as you\u2019ve put it, \u201cwe wanted Rosie the robot, and instead we got the roomba.\u201d So you\u2019ve advocated for bringing psychology back into the mix, because there\u2019s a lot of things that humans do better, and that we should be studying humans to understand why they do things better. Is this still how you feel about the field?<\/strong><\/p>\n<p class=\"m_4570964794744971347gmail-graf m_4570964794744971347gmail-graf--p\">GM: Pretty much. There was probably a little more low hanging fruit than I anticipated. I saw somebody else say it more concisely, which is simply, deep learning does not equal AGI (AGI is \u201cartificial general intelligence.\u201d) There\u2019s all the stuff you can do with deep learning, like it makes your speech recognition better. It makes your object recognition better. But that doesn\u2019t mean it\u2019s intelligence. Intelligence is a multi-dimensional variable. There are lots of things that go into it.<\/p>\n<p class=\"m_4570964794744971347gmail-graf m_4570964794744971347gmail-graf--p\"><a>In a talk I gave at TEDx CERN<\/a> recently, I made this kind of pie chart and I said look, here\u2019s perception that\u2019s a tiny slice of the pie. It\u2019s an important slice of the pie, but there\u2019s lots of other things that go into human intelligence, like our ability to attend to the right things at the same time, to reason about them to build models of what\u2019s going on in order to anticipate what might happen next and so forth. And perception is just a piece of it. And deep learning is really just helping with that piece.<\/p>\n<aside class=\"inset inset-sm inset-section\">\n<section class=\"aside section video-aside crunchreport collapse collapse-adjacent\" data-video-id=\"58dee38a83b51f481b57ffc4\">\n<h2 class=\"collapse-title section-title\">Latest <span>Crunch Report<\/span><\/h2>\n<div class=\"collapse-body cf\">\n<ul class=\"vid-list cf\">\n<li class=\"block vid-feature\" data-lightbox-omniture=\"crunchreport\" readability=\"-2\">\n<div class=\"block block-inset\" readability=\"7\"><a href=\"https:\/\/techcrunch.com\/video\/spacex-successfully-re-launches-a-rocket-crunch-report\/58dee38a83b51f481b57ffc4\/?ncid=rightrail_cr\"><img decoding=\"async\" src=\"https:\/\/img.vidible.tv\/prod\/2017-03\/31\/58dee38a83b51f481b57ffc4\/58dee424c7480e35f58cd31c_o_U_v1.jpg?w=300&#038;h=170\" alt=\"SpaceX Successfully Re-launches a Rocket | Crunch Report\" data-lightbox-url=\"https:\/\/techcrunch.com\/video\/spacex-successfully-re-launches-a-rocket-crunch-report\/58dee38a83b51f481b57ffc4\/lightbox\"\/><\/a><\/p>\n<p><h3>SpaceX Successfully Re-launches a Rocket | Crunch Report<\/h3>\n<\/p>\n<\/div>\n<\/li>\n<\/ul>\n<p><a href=\"https:\/\/techcrunch.com\/video\/crunchreport\/?ncid=rightrail_crmore\" class=\"text-btn\" data-omni-sm=\"rightrail_crmore\">Watch More Episodes<\/a><\/div>\n<\/section>\n<\/aside>\n<p class=\"m_4570964794744971347gmail-graf m_4570964794744971347gmail-graf--p\"><a>In a New Yorker article that I wrote in 2012<\/a>, I said look, this is great, but it\u2019s not really helping us solve causal understanding. It\u2019s not really helping with language. Just because you\u2019ve built a better ladder doesn\u2019t mean you\u2019ve gotten to the moon. I still feel that way. I still feel like we\u2019re actually no closer to the moon, where the moonshot is intelligence that\u2019s really as flexible as human beings. We\u2019re no closer to that moonshot than we were four years ago. There\u2019s all this excitement about AI and it\u2019s well deserved. AI is a practical tool for the first time and that\u2019s great. There\u2019s good reason for companies to put in all of this money. But just look for example at a driverless car, that\u2019s a form of intelligence, modest intelligence, the average 16-year-old can do it as long as they\u2019re sober, with a couple of months of training. Yet Google has worked on it for seven years and their car still can only drive\u200a\u2014\u200a as far as I can tell since they don\u2019t publish the data\u200a\u2014\u200alike on sunny days, without too much traffic\u2026<\/p>\n<p class=\"m_4570964794744971347gmail-graf m_4570964794744971347gmail-graf--p\"><strong class=\"m_4570964794744971347gmail-markup--strong m_4570964794744971347gmail-markup--p-strong\">AMLG: And isn\u2019t there the whole black box problem that you don\u2019t know what\u2019s going on. We don\u2019t know the inner workings of deep learning, it\u2019s kind of inscrutable. Isn\u2019t that a massive problem for things like driverless cars?<\/strong><\/p>\n<p class=\"m_4570964794744971347gmail-graf m_4570964794744971347gmail-graf--p\">GM: It is a problem. Whether it\u2019s an insuperable problem is an open empirical question. So it is a fact at least for now that we can\u2019t well interpret what deep learning is doing. So the way to think about it is you have millions of parameters and millions of data points. That means that if I as an engineer look at this thing I have to contend with these millions or billions of numbers that have been set based on all of that data and maybe there is a kind of rhyme or reason to it but it\u2019s not obvious and there\u2019s some good theoretical arguments to think sometimes you\u2019re never really going to find an interpretable answer there.<\/p>\n<p class=\"m_4570964794744971347gmail-graf m_4570964794744971347gmail-graf--p\">There\u2019s an argument now in the literature which goes back to some work that I was doing in the 90s about whether deep learning is just memorization. So this was the paper that came out that said it is and another says no it isn\u2019t. Well it isn\u2019t literally exactly memorization but it\u2019s a little bit like that. If you memorize all these examples, there may not be some abstract rule that characterizes all of what\u2019s going on but it might be hard to say what\u2019s there. So if you build your system entirely with deep learning, which is something that Nvidia has played around with, and something goes wrong, it\u2019s hard to know what\u2019s going on and that makes it hard to debug.<\/p>\n<p class=\"m_4570964794744971347gmail-graf m_4570964794744971347gmail-graf--p\"><strong class=\"m_4570964794744971347gmail-markup--strong m_4570964794744971347gmail-markup--p-strong\">AMLG: Which is a problem if your car just runs into a lamppost and you can\u2019t debug why that happened.<\/strong><\/p>\n<p class=\"m_4570964794744971347gmail-graf m_4570964794744971347gmail-graf--p\">GM: You\u2019re lucky if it\u2019s only a lamppost and not too many people are injured. There are serious risks here. Somebody did die, though I think it wasn\u2019t a deep learning system in <a>the Tesla crash<\/a>, it was a different kind of system. We actually have problems on engineering on both ends. So I don\u2019t want to say that classical AI has fully licked these problems, it hasn\u2019t. I think it\u2019s been abandoned prematurely and people should come back to it. But the fact is we don\u2019t have good ways of engineering really complex systems. And minds are really complex systems.<\/p>\n<p class=\"m_4570964794744971347gmail-graf m_4570964794744971347gmail-graf--p\"><strong class=\"m_4570964794744971347gmail-markup--strong m_4570964794744971347gmail-markup--p-strong\">AMLG: Why do you think these big platforms are reorganizing around AI and specifically deep learning. Is it just that they\u2019ve got data moats, so you might as well train on all of that data if you\u2019ve got it?<\/strong><\/p>\n<p class=\"m_4570964794744971347gmail-graf m_4570964794744971347gmail-graf--p\">GM: Well there\u2019s an interesting thing about Google which is they have enormous amounts of data. So of course they want to leverage it. Google has the power to build new resources that they give away free and they build the resources that are particular to their problem. So Google because they have this massive amount of data has oriented their AI around, how can I leverage that data? Which makes sense from their commercial interests. But it doesn\u2019t necessarily mean, say from a society\u2019s perspective. does society need AI? What does it need it for? Would be the best way to build it?<\/p>\n<p class=\"m_4570964794744971347gmail-graf m_4570964794744971347gmail-graf--p\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-1471800\" src=\"https:\/\/tctechcrunch2011.files.wordpress.com\/2017\/04\/unnamed-8.png?w=679&#038;h=380\" alt=\"\" width=\"679\" height=\"380\" srcset=\"https:\/\/tctechcrunch2011.files.wordpress.com\/2017\/04\/unnamed-8.png?w=677&#038;h=380 677w, https:\/\/tctechcrunch2011.files.wordpress.com\/2017\/04\/unnamed-8.png?w=150&#038;h=84 150w, https:\/\/tctechcrunch2011.files.wordpress.com\/2017\/04\/unnamed-8.png?w=300&#038;h=168 300w, https:\/\/tctechcrunch2011.files.wordpress.com\/2017\/04\/unnamed-8.png?w=768&#038;h=431 768w, https:\/\/tctechcrunch2011.files.wordpress.com\/2017\/04\/unnamed-8.png?w=680&#038;h=382 680w, https:\/\/tctechcrunch2011.files.wordpress.com\/2017\/04\/unnamed-8.png 960w\" sizes=\"(max-width: 679px) 100vw, 679px\"\/><\/p>\n<div class=\"pullquote-wrap right\" readability=\"10\">\n<blockquote class=\"pullquote\" readability=\"13\">\n<p>\u201cCERN is a vast interdisciplinary, multi-country consortium to solve particular scientific problems, maybe we need the same thing for AI. Most of the efforts in AI right now are individual companies or small labs working on small problems like how to sell more advertising\u2026 what if we brought people together to try this moonshot of doing better science, and what if we brought not just machine learning experts, and engineers who can make faster hardware, but researchers who look at cognitive development. I think we could make some progress\u201d\u200a<\/p>\n<\/blockquote>\n<p><span class=\"pullquote-author-pos\">\u2014 Gary Marcus<\/span><\/div>\n<aside class=\"inset inset-sm inset-section\"\/>\n<p class=\"m_4570964794744971347gmail-graf m_4570964794744971347gmail-graf--p\">I think if you asked those questions you would say, well what society most needs is automated scientific discovery that can help us actually understand the brain to cure neural disorders, to actually understand cancer to cure cancer, and so forth. If that were the thing we were most trying to solve in AI, I think we would say, let\u2019s not leave it all in the hands of these companies. Let\u2019s have an international consortium kind of like we had for CERN, the large hadron collider. That\u2019s seven billion dollars. What if you had $7 billion dollars that was carefully orchestrated towards a common goal. You could imagine society taking that approach. It\u2019s not going to happen right now given the current political climate.<\/p>\n<p class=\"m_4570964794744971347gmail-graf m_4570964794744971347gmail-graf--p\"><strong class=\"m_4570964794744971347gmail-markup--strong m_4570964794744971347gmail-markup--p-strong\">AMLG: Well they are sort of at least coming together on AI ethics. So that\u2019s a start.<\/strong><\/p>\n<p class=\"m_4570964794744971347gmail-graf m_4570964794744971347gmail-graf--p\">GM: It is good that people are talking about the ethical issues and there are serious issues that deserve consideration. The only thing I would say there is, some people are hysterical about it, thinking that real AI is around the corner and it probably isn\u2019t. I think it\u2019s still OK that we start thinking about these things now, even if real AI is further away than people think it is. If that\u2019s what moves people into action and it takes 20 years, but the action itself takes 20 years, then it\u2019s the right timing to start thinking about it now.<\/p>\n<p class=\"m_4570964794744971347gmail-graf m_4570964794744971347gmail-graf--p\"><strong class=\"m_4570964794744971347gmail-markup--strong m_4570964794744971347gmail-markup--p-strong\">AMLG: I want to get back to your alternative approach to solving AI, and why it\u2019s so important. So you\u2019ve come up with what you believe is a better paradigm, taking inspiration from cognitive psychology. The idea is that your algorithms are a much quicker study, that they\u2019re more efficient and less data hungry, less brittle and that they can have broader applicability. And in a brief amount of time you\u2019ve had impressive early results. You\u2019ve run a bunch of image recognition tests comparing the techniques and have shown that your algorithms perform better, using smaller amounts of data, often called sparse data.\u00a0<\/strong><strong class=\"m_4570964794744971347gmail-markup--strong m_4570964794744971347gmail-markup--p-strong\">So deep learning works well when you have tons of data for common examples and high frequency things. But in the real world, in most domains, there\u2019s a long tail of things where there isn\u2019t a lot of data. So while neural nets may be good at low level perception, they aren\u2019t as good at understanding integrated wholes. So tell us more about your approach, and how your training in cognitive neuroscience has informed it?<\/strong><\/p>\n<p class=\"m_4570964794744971347gmail-graf m_4570964794744971347gmail-graf--p\">GM: My training was with Steve Pinker. And through that training I became sensitive to the fact that human children are very good at learning language, phenomenally good, even when they\u2019re not that good at other things. Of course I read about that as a graduate student, now I have some human children, I have a four-year-old and a two-and-a-half year old. And it\u2019s just amazing how fast they learn.<\/p>\n<p class=\"m_4570964794744971347gmail-graf m_4570964794744971347gmail-graf--p\"><strong class=\"m_4570964794744971347gmail-markup--strong m_4570964794744971347gmail-markup--p-strong\">AMLG: The best AI\u2019s you\u2019ve ever seen.<\/strong><\/p>\n<p class=\"m_4570964794744971347gmail-graf m_4570964794744971347gmail-graf--p\">GM: The best AI\u2019s I\u2019ve ever seen. Actually my son shares a birthday with Rodney Brooks, who\u2019s one of the great roboticists, I think you know him well. For a while I was sending Rodney an e-mail message every year saying \u201chappy birthday. My son is now a year old. I think he can do this and your robots can\u2019t.\u201d It was kind of a running joke between us.<\/p>\n<p class=\"m_4570964794744971347gmail-graf m_4570964794744971347gmail-graf--p\"><strong class=\"m_4570964794744971347gmail-markup--strong m_4570964794744971347gmail-markup--p-strong\">AMLG: And now he\u2019s vastly superior to all of the robots.<\/strong><\/p>\n<p class=\"m_4570964794744971347gmail-graf m_4570964794744971347gmail-graf--p\">GM: And I didn\u2019t even bother this year. The four year olds of this world, what they can do in terms of motor control and language is far ahead of what robots can do. And so I started thinking about that kind of question really in the early 90s. and I\u2019ve never fully figured out the answer but part of the motivation for my company was, hey we have these systems now that are pretty good at learning if you have gigabytes of data and that\u2019s great work if you can get it, and you can get it sometimes. So speech recognition, if you\u2019re talking about white males asking search queries in a quiet room, you can get as much labelled data, which is critical, for these systems as you want. This is how somebody says something and this is the word written out. But my kids don\u2019t need that. They don\u2019t have labelled data, they don\u2019t have gigabytes of label data they just kind of watch the world and they figure all this stuff out.<\/p>\n<div id=\"attachment_1471802\" class=\"wp-caption aligncenter c7\" readability=\"18.929577464789\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-1471802\" src=\"https:\/\/tctechcrunch2011.files.wordpress.com\/2017\/04\/unnamed-9.png?w=759&#038;h=577\" alt=\"\" width=\"759\" height=\"577\" srcset=\"https:\/\/tctechcrunch2011.files.wordpress.com\/2017\/04\/unnamed-9.png 733w, https:\/\/tctechcrunch2011.files.wordpress.com\/2017\/04\/unnamed-9.png?w=150&#038;h=114 150w, https:\/\/tctechcrunch2011.files.wordpress.com\/2017\/04\/unnamed-9.png?w=300&#038;h=228 300w, https:\/\/tctechcrunch2011.files.wordpress.com\/2017\/04\/unnamed-9.png?w=680&#038;h=518 680w\" sizes=\"(max-width: 759px) 100vw, 759px\"\/><\/p>\n<p class=\"wp-caption-text\"><a target=\"_blank\" href=\"https:\/\/www.technologyreview.com\/s\/601551\/algorithms-that-learn-with-less-data-could-expand-ais-power\/\">Geometric\u2019s Xprop algorithm<\/a> systematically beating convolutional nets<\/p>\n<\/div>\n<p><small>Featured Image: <a target=\"_blank\" href=\"http:\/\/www.shutterstock.com\/gallery-553555p1.html\">agsandrew<\/a>\/<a target=\"_blank\" href=\"http:\/\/www.shutterstock.com\">Shutterstock<\/a><\/small> <\/p>\n","protected":false},"excerpt":{"rendered":"<p><img loading=\"lazy\" decoding=\"async\" width=\"680\" height=\"383\" src=\"https:\/\/tctechcrunch2011.files.wordpress.com\/2016\/02\/shutterstock_147776027.jpg?w=680\" class=\"attachment-large size-large wp-post-image\" alt=\"\" srcset=\"https:\/\/tctechcrunch2011.files.wordpress.com\/2016\/02\/shutterstock_147776027.jpg?w=680 680w, https:\/\/tctechcrunch2011.files.wordpress.com\/2016\/02\/shutterstock_147776027.jpg?w=1360 1360w, https:\/\/tctechcrunch2011.files.wordpress.com\/2016\/02\/shutterstock_147776027.jpg?w=150 150w, https:\/\/tctechcrunch2011.files.wordpress.com\/2016\/02\/shutterstock_147776027.jpg?w=300 300w, https:\/\/tctechcrunch2011.files.wordpress.com\/2016\/02\/shutterstock_147776027.jpg?w=768 768w\" sizes=\"(max-width: 680px) 100vw, 680px\" \/>&nbsp;It&#8217;s hard to visit a tech site these days without seeing a headline about deep learning for X, and that AI is on the verge of solving all our problems. Gary Marcus remains skeptical. Marcus, a best-selling author, entrepreneur, and professor of psychology at NYU, has spent decades studying how children learn and believes that throwing more data at problems won&#8217;t necessarily lead&hellip; <a href=\"https:\/\/techcrunch.com\/2017\/04\/01\/discussing-the-limits-of-artificial-intelligence\/?ncid=rss\">Read More<\/a><\/p>\n<div class=\"feedflare\">\n<a href=\"http:\/\/feeds.feedburner.com\/~ff\/Techcrunch?a=h4EZ2s-WurY:ntKzP5sWnpQ:2mJPEYqXBVI\"><img decoding=\"async\" src=\"http:\/\/feeds.feedburner.com\/~ff\/Techcrunch?d=2mJPEYqXBVI\" border=\"0\"><\/img><\/a> <a href=\"http:\/\/feeds.feedburner.com\/~ff\/Techcrunch?a=h4EZ2s-WurY:ntKzP5sWnpQ:7Q72WNTAKBA\"><img decoding=\"async\" src=\"http:\/\/feeds.feedburner.com\/~ff\/Techcrunch?d=7Q72WNTAKBA\" border=\"0\"><\/img><\/a> <a href=\"http:\/\/feeds.feedburner.com\/~ff\/Techcrunch?a=h4EZ2s-WurY:ntKzP5sWnpQ:yIl2AUoC8zA\"><img decoding=\"async\" src=\"http:\/\/feeds.feedburner.com\/~ff\/Techcrunch?d=yIl2AUoC8zA\" border=\"0\"><\/img><\/a> <a href=\"http:\/\/feeds.feedburner.com\/~ff\/Techcrunch?a=h4EZ2s-WurY:ntKzP5sWnpQ:-BTjWOF_DHI\"><img decoding=\"async\" src=\"http:\/\/feeds.feedburner.com\/~ff\/Techcrunch?i=h4EZ2s-WurY:ntKzP5sWnpQ:-BTjWOF_DHI\" border=\"0\"><\/img><\/a> <a href=\"http:\/\/feeds.feedburner.com\/~ff\/Techcrunch?a=h4EZ2s-WurY:ntKzP5sWnpQ:D7DqB2pKExk\"><img decoding=\"async\" src=\"http:\/\/feeds.feedburner.com\/~ff\/Techcrunch?i=h4EZ2s-WurY:ntKzP5sWnpQ:D7DqB2pKExk\" border=\"0\"><\/img><\/a> <a href=\"http:\/\/feeds.feedburner.com\/~ff\/Techcrunch?a=h4EZ2s-WurY:ntKzP5sWnpQ:qj6IDK7rITs\"><img decoding=\"async\" src=\"http:\/\/feeds.feedburner.com\/~ff\/Techcrunch?d=qj6IDK7rITs\" border=\"0\"><\/img><\/a>\n<\/div>\n<p><img loading=\"lazy\" decoding=\"async\" src=\"http:\/\/feeds.feedburner.com\/~r\/Techcrunch\/~4\/h4EZ2s-WurY\" height=\"1\" width=\"1\" alt=\"\"\/> <\/p>\n","protected":false},"author":5817,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[25],"tags":[59,66,26],"class_list":["post-337389","post","type-post","status-publish","format-standard","hentry","category-technology","tag-media","tag-techcrunch","tag-technology"],"_links":{"self":[{"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/posts\/337389","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/users\/5817"}],"replies":[{"embeddable":true,"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/comments?post=337389"}],"version-history":[{"count":0,"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/posts\/337389\/revisions"}],"wp:attachment":[{"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/media?parent=337389"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/categories?post=337389"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/people.utm.my\/asmawisham\/wp-json\/wp\/v2\/tags?post=337389"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}