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	<title>Gigaom Search &#187; Technologies and Products &#187; deep learning</title>
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		<title>How PayPal uses deep learning and detective work to fight fraud</title>
		<link>http://gigaom.com/2015/03/06/how-paypal-uses-deep-learning-and-detective-work-to-fight-fraud/</link>
		<comments>http://gigaom.com/2015/03/06/how-paypal-uses-deep-learning-and-detective-work-to-fight-fraud/#comments</comments>
		<pubDate>Fri, 06 Mar 2015 20:32:34 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[fraud]]></category>
		<category><![CDATA[Internet fraud]]></category>
		<category><![CDATA[machine-learning]]></category>
		<category><![CDATA[online payment platform]]></category>
		<category><![CDATA[Pattern recognition]]></category>
<category domain="http://search.gigaom.com/stock/"><![CDATA[NASDAQ:FB]]></category>
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		<guid isPermaLink="false">http://gigaom.com/?p=919400</guid>
		<description><![CDATA[Hui Wang has seen the nature of online fraud change a lot in the 11 years she's been at PayPal. In fact, a continuous evolution of methods is kind of the nature of&#8230;]]></description>
		<wfw:commentRss>http://gigaom.com/2015/03/06/how-paypal-uses-deep-learning-and-detective-work-to-fight-fraud/feed/</wfw:commentRss>
		<slash:comments>2</slash:comments>
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		<title>IBM acquires deep learning startup AlchemyAPI</title>
		<link>http://gigaom.com/2015/03/04/ibm-acquires-deep-learning-startup-alchemyapi/</link>
		<comments>http://gigaom.com/2015/03/04/ibm-acquires-deep-learning-startup-alchemyapi/#comments</comments>
		<pubDate>Wed, 04 Mar 2015 16:15:56 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[ibm-watson]]></category>
		<category><![CDATA[machine-learning]]></category>
		<category><![CDATA[Watson]]></category>
<category domain="http://search.gigaom.com/stock/"><![CDATA[NYSE:IBM]]></category>
		
		<guid isPermaLink="false">http://gigaom.com/?p=918762</guid>
		<description><![CDATA[So much for AlchemyAPI CEO Elliot Turner's statement that his company is not for sale. IBM has bought the Denver-based deep learning startup that delivers a wide variety of text analysis&#8230;]]></description>
		<wfw:commentRss>http://gigaom.com/2015/03/04/ibm-acquires-deep-learning-startup-alchemyapi/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
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		<item>
		<title>Google, Stanford say big data is key to deep learning for drug discovery</title>
		<link>http://gigaom.com/2015/03/02/google-stanford-say-big-data-is-key-to-deep-learning-for-drug-discovery/</link>
		<comments>http://gigaom.com/2015/03/02/google-stanford-say-big-data-is-key-to-deep-learning-for-drug-discovery/#comments</comments>
		<pubDate>Mon, 02 Mar 2015 20:22:11 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[drug discovery]]></category>
		<category><![CDATA[machine-learning]]></category>
		<category><![CDATA[medical data]]></category>
		<category><![CDATA[pharmaceutical industry]]></category>
<category domain="http://search.gigaom.com/stock/"><![CDATA[NASDAQ:GOOG]]></category>
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		<category domain="http://search.gigaom.com/stock/"><![CDATA[NYSE:IBM]]></category>
		
		<guid isPermaLink="false">http://gigaom.com/?p=918172</guid>
		<description><![CDATA[A team of researchers from Stanford University and Google have released a paper highlighting a deep learning approach they say shows promise in the field of drug discovery. What they found, essentially, is that&#8230;]]></description>
		<wfw:commentRss>http://gigaom.com/2015/03/02/google-stanford-say-big-data-is-key-to-deep-learning-for-drug-discovery/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
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		<title>Microsoft is building fast, low-power neural networks with FPGAs</title>
		<link>http://gigaom.com/2015/02/23/microsoft-is-building-fast-low-power-neural-networks-with-fpgas/</link>
		<comments>http://gigaom.com/2015/02/23/microsoft-is-building-fast-low-power-neural-networks-with-fpgas/#comments</comments>
		<pubDate>Mon, 23 Feb 2015 17:28:12 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Altera]]></category>
		<category><![CDATA[FPGAs]]></category>
		<category><![CDATA[machine learning]]></category>
		<category><![CDATA[Microsoft Research]]></category>
		<category><![CDATA[neural networks]]></category>
		<category><![CDATA[object recognition]]></category>
		<category><![CDATA[processor architecture]]></category>
		<category><![CDATA[web scale]]></category>
		<category><![CDATA[webscale infrastructure]]></category>
<category domain="http://search.gigaom.com/stock/"><![CDATA[NASDAQ:MSFT]]></category>
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		<guid isPermaLink="false">http://gigaom.com/?p=916437</guid>
		<description><![CDATA[Microsoft on Monday released a white paper explaining a current effort to run convolutional neural networks -- the deep learning technique responsible for record-setting computer vision algorithms -- on FPGAs rather&#8230;]]></description>
		<wfw:commentRss>http://gigaom.com/2015/02/23/microsoft-is-building-fast-low-power-neural-networks-with-fpgas/feed/</wfw:commentRss>
		<slash:comments>1</slash:comments>
		</item>
		<item>
		<title>Remember when machine learning was hard? That&#8217;s about to change</title>
		<link>http://gigaom.com/2015/02/21/remember-when-machine-learning-was-hard-thats-about-to-change/</link>
		<comments>http://gigaom.com/2015/02/21/remember-when-machine-learning-was-hard-thats-about-to-change/#comments</comments>
		<pubDate>Sat, 21 Feb 2015 17:56:40 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[machine learning]]></category>
		<category><![CDATA[Structure Data 2015]]></category>
<category domain="http://search.gigaom.com/stock/"><![CDATA[NASDAQ:MSFT]]></category>
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		<guid isPermaLink="false">http://gigaom.com/?p=916311</guid>
		<description><![CDATA[A few years ago, there was a shift in the world of machine learning. Companies, such as Skytree and Context Relevant, began popping up, promising to make it easier for companies&#8230;]]></description>
		<wfw:commentRss>http://gigaom.com/2015/02/21/remember-when-machine-learning-was-hard-thats-about-to-change/feed/</wfw:commentRss>
		<slash:comments>1</slash:comments>
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		<item>
		<title>AWS suits up more enterprise perks</title>
		<link>http://gigaom.com/2015/02/15/aws-suits-up-more-enterprise-perks/</link>
		<comments>http://gigaom.com/2015/02/15/aws-suits-up-more-enterprise-perks/#comments</comments>
		<pubDate>Sun, 15 Feb 2015 17:42:52 +0000</pubDate>
		<dc:creator><![CDATA[Barb Darrow]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[AWS Config]]></category>
		<category><![CDATA[AWS Service Catalog]]></category>
		<category><![CDATA[OpenStack]]></category>
<category domain="http://search.gigaom.com/stock/"><![CDATA[NASDAQ:AMZN]]></category>
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		<guid isPermaLink="false">http://gigaom.com/?p=915115</guid>
		<description><![CDATA[More AWS perks for business users Amazon Web Services has beefed up its identity management and access control capabilities so that businesses can more easily apply permissions to users, groups and&#8230;]]></description>
		<wfw:commentRss>http://gigaom.com/2015/02/15/aws-suits-up-more-enterprise-perks/feed/</wfw:commentRss>
		<slash:comments>2</slash:comments>
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		</item>
		<item>
		<title>Why deep learning is at least inspired by biology, if not the brain</title>
		<link>http://gigaom.com/2015/02/14/why-deep-learning-is-at-least-inspired-by-biology-if-not-the-brain/</link>
		<comments>http://gigaom.com/2015/02/14/why-deep-learning-is-at-least-inspired-by-biology-if-not-the-brain/#comments</comments>
		<pubDate>Sat, 14 Feb 2015 18:58:13 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Computational neuroscience]]></category>
		<category><![CDATA[Enlitic]]></category>
		<category><![CDATA[health care]]></category>
		<category><![CDATA[healthcare]]></category>
		<category><![CDATA[machine learning]]></category>
		<category><![CDATA[neuroscience]]></category>
		<category><![CDATA[object recognition]]></category>

		<guid isPermaLink="false">http://gigaom.com/?p=915084</guid>
		<description><![CDATA[As deep learning continues gathering steam among researchers, entrepreneurs and the press, there's a loud-and-getting-louder debate about whether its algorithms actually operate like the human brain does. The comparison might not make much&#8230;]]></description>
		<wfw:commentRss>http://gigaom.com/2015/02/14/why-deep-learning-is-at-least-inspired-by-biology-if-not-the-brain/feed/</wfw:commentRss>
		<slash:comments>4</slash:comments>
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		<item>
		<title>Microsoft says its new computer vision system can outperform humans</title>
		<link>http://gigaom.com/2015/02/13/microsoft-says-its-new-computer-vision-system-can-outperform-humans/</link>
		<comments>http://gigaom.com/2015/02/13/microsoft-says-its-new-computer-vision-system-can-outperform-humans/#comments</comments>
		<pubDate>Fri, 13 Feb 2015 19:17:35 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[image recognition]]></category>
		<category><![CDATA[machine learning]]></category>
		<category><![CDATA[Microsoft Research]]></category>
		<category><![CDATA[object recognition]]></category>
		<category><![CDATA[Structure Data 2015]]></category>
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		<guid isPermaLink="false">http://gigaom.com/?p=914914</guid>
		<description><![CDATA[Microsoft researchers claim in a recently published paper that they have developed the first computer system capable of outperforming humans on a popular benchmark. While it's estimated that humans can classify images in&#8230;]]></description>
		<wfw:commentRss>http://gigaom.com/2015/02/13/microsoft-says-its-new-computer-vision-system-can-outperform-humans/feed/</wfw:commentRss>
		<slash:comments>6</slash:comments>
		</item>
		<item>
		<title>No, you don&#8217;t need a ton of data to do deep learning</title>
		<link>http://gigaom.com/2015/02/12/no-you-dont-need-a-ton-of-data-to-do-deep-learning/</link>
		<comments>http://gigaom.com/2015/02/12/no-you-dont-need-a-ton-of-data-to-do-deep-learning/#comments</comments>
		<pubDate>Thu, 12 Feb 2015 08:01:33 +0000</pubDate>
		<dc:creator><![CDATA[Barb Darrow]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Enlitic]]></category>
		<category><![CDATA[Jeremy Howard]]></category>
		<category><![CDATA[Structure Show]]></category>
		<category><![CDATA[The Structure Show]]></category>
<category domain="http://search.gigaom.com/stock/"><![CDATA[NASDAQ:AMZN]]></category>
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		<category domain="http://search.gigaom.com/stock/"><![CDATA[NYSE:IBM]]></category>
		
		<guid isPermaLink="false">http://gigaom.com/?p=914355</guid>
		<description><![CDATA[[soundcloud url="https://api.soundcloud.com/tracks/190680894" params="secret_token=s-lutIw&#38;color=ff5500&#38;auto_play=false&#38;hide_related=false&#38;show_comments=true&#38;show_user=true&#38;show_reposts=false" width="100%" height="166" iframe="true" /] There are a couple of seemingly contradictory memes rolling around the deep learning field. One is that you need a truly epic amount of data to&#8230;]]></description>
		<wfw:commentRss>http://gigaom.com/2015/02/12/no-you-dont-need-a-ton-of-data-to-do-deep-learning/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
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		</item>
		<item>
		<title>Gigaom’s new AI and deep learning conference: Structure Intelligence</title>
		<link>https://gigaom.com/2015/02/10/gigaoms-new-ai-and-deep-learning-conference-structure-intelligence/</link>
		<comments>https://gigaom.com/2015/02/10/gigaoms-new-ai-and-deep-learning-conference-structure-intelligence/#comments</comments>
		<pubDate>Tue, 10 Feb 2015 15:30:16 +0000</pubDate>
		<dc:creator><![CDATA[Clare Ryan]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Structure Intelligence]]></category>

		<guid isPermaLink="false">http://gigaom.com/?p=913716</guid>
		<description><![CDATA[We are thrilled to announce the launch of Gigaom’s newest conference, Structure Intelligence. In the past year we’ve seen massive growth in Artificial Intelligence (AI) and deep learning. Our own Derrick&#8230;]]></description>
		<wfw:commentRss>https://gigaom.com/2015/02/10/gigaoms-new-ai-and-deep-learning-conference-structure-intelligence/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
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