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	<title>Gigaom Search &#187; neural networks</title>
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		<title>A look at Zeroth, Qualcomm’s effort to put AI in your smartphone</title>
		<link>http://gigaom.com/2015/03/03/a-look-at-zeroth-qualcomms-effort-to-put-ai-in-your-smartphone/</link>
		<comments>http://gigaom.com/2015/03/03/a-look-at-zeroth-qualcomms-effort-to-put-ai-in-your-smartphone/#comments</comments>
		<pubDate>Tue, 03 Mar 2015 15:08:09 +0000</pubDate>
		<dc:creator><![CDATA[Kevin Fitchard]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[machine-learning]]></category>
		<category><![CDATA[Mobile World Congress]]></category>
		<category><![CDATA[Mobile World Congress (MWC)]]></category>
		<category><![CDATA[MWC]]></category>
		<category><![CDATA[MWC 2015]]></category>
		<category><![CDATA[neural networks]]></category>
		<category><![CDATA[Structure Data 2015]]></category>
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		<guid isPermaLink="false">http://gigaom.com/?p=918382</guid>
		<description><![CDATA[What if your smartphone camera were smart enough to identify that the plate of clams and black beans appearing in its lens was actually food? What if it then automatically could&#8230;]]></description>
		<wfw:commentRss>http://gigaom.com/2015/03/03/a-look-at-zeroth-qualcomms-effort-to-put-ai-in-your-smartphone/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
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		<item>
		<title>Breakthrough in FPGAs could make custom chips faster, larger</title>
		<link>http://gigaom.com/2015/02/27/breakthrough-in-fpgas-could-make-custom-chips-faster-larger/</link>
		<comments>http://gigaom.com/2015/02/27/breakthrough-in-fpgas-could-make-custom-chips-faster-larger/#comments</comments>
		<pubDate>Fri, 27 Feb 2015 16:31:33 +0000</pubDate>
		<dc:creator><![CDATA[Stacey Higginbotham]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[communications space]]></category>
		<category><![CDATA[Computer architecture]]></category>
		<category><![CDATA[Field-programmable gate array]]></category>
		<category><![CDATA[microprocessors]]></category>
		<category><![CDATA[neural networks]]></category>
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		<guid isPermaLink="false">http://gigaom.com/?p=917653</guid>
		<description><![CDATA[Today we are worshipping the gods of the algorithm, according to one prominent magazine. It's not a bad comparison. Everything from search results to our machine learning efforts are the basis&#8230;]]></description>
		<wfw:commentRss>http://gigaom.com/2015/02/27/breakthrough-in-fpgas-could-make-custom-chips-faster-larger/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>Microsoft&#8217;s machine learning guru on why data matters sooooo much</title>
		<link>http://gigaom.com/2015/02/19/microsofts-machine-learning-guru-on-why-data-matters-sooooo-much/</link>
		<comments>http://gigaom.com/2015/02/19/microsofts-machine-learning-guru-on-why-data-matters-sooooo-much/#comments</comments>
		<pubDate>Thu, 19 Feb 2015 18:20:03 +0000</pubDate>
		<dc:creator><![CDATA[Barb Darrow]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Azure ML]]></category>
		<category><![CDATA[HDInsigh]]></category>
		<category><![CDATA[machine learning]]></category>
		<category><![CDATA[neural networks]]></category>
		<category><![CDATA[Structure Show]]></category>
		<category><![CDATA[The Structure Show]]></category>
<category domain="http://search.gigaom.com/stock/"><![CDATA[NASDAQ:MSFT]]></category>
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		<guid isPermaLink="false">http://gigaom.com/?p=915757</guid>
		<description><![CDATA[[soundcloud url="https://api.soundcloud.com/tracks/191875439" params="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" /] Not surprisingly, Joseph Sirosh, has big ambitions for his product portfolio at Microsoft which includes Azure ML, HDInsight and other tools. Chief among them is&#8230;]]></description>
		<wfw:commentRss>http://gigaom.com/2015/02/19/microsofts-machine-learning-guru-on-why-data-matters-sooooo-much/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
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		<title>How AI can help build a universal real-time translator</title>
		<link>https://gigaom.com/2015/01/29/how-ai-can-help-build-a-universal-real-time-translator/</link>
		<comments>https://gigaom.com/2015/01/29/how-ai-can-help-build-a-universal-real-time-translator/#comments</comments>
		<pubDate>Thu, 29 Jan 2015 17:47:05 +0000</pubDate>
		<dc:creator><![CDATA[Stacey Higginbotham]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Artificial neural network]]></category>
		<category><![CDATA[Geoffrey Hinton]]></category>
		<category><![CDATA[neural networks]]></category>
		<category><![CDATA[Recurrent neural network]]></category>
<category domain="http://search.gigaom.com/stock/"><![CDATA[NASDAQ:GOOG]]></category>
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		<guid isPermaLink="false">http://gigaom.com/?p=910852</guid>
		<description><![CDATA[The breakthroughs in natural language processing and machine translation brought by deep learning might enable us to build a trope of science-fiction books -- a universal real-time translator that fits within&#8230;]]></description>
		<wfw:commentRss>https://gigaom.com/2015/01/29/how-ai-can-help-build-a-universal-real-time-translator/feed/</wfw:commentRss>
		<slash:comments>3</slash:comments>
		</item>
		<item>
		<title>Facebook open sources tools for bigger, faster deep learning models</title>
		<link>https://gigaom.com/2015/01/16/facebook-open-sources-tools-for-bigger-faster-deep-learning-models/</link>
		<comments>https://gigaom.com/2015/01/16/facebook-open-sources-tools-for-bigger-faster-deep-learning-models/#comments</comments>
		<pubDate>Fri, 16 Jan 2015 16:10:58 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[machine learning]]></category>
		<category><![CDATA[neural networks]]></category>
		<category><![CDATA[open source]]></category>
<category domain="http://search.gigaom.com/stock/"><![CDATA[NASDAQ:FB]]></category>
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		<guid isPermaLink="false">http://gigaom.com/?p=907116</guid>
		<description><![CDATA[Facebook on Friday open sourced a handful of software libraries that it claims will help users build bigger, faster deep learning models than existing tools allow. The libraries, which  is&#8230;]]></description>
		<wfw:commentRss>https://gigaom.com/2015/01/16/facebook-open-sources-tools-for-bigger-faster-deep-learning-models/feed/</wfw:commentRss>
		<slash:comments>5</slash:comments>
		</item>
		<item>
		<title>This company says it can fix the sales process using lots of data science, and even more data</title>
		<link>https://gigaom.com/2014/10/10/this-company-says-it-can-fix-the-sales-process-using-lots-of-data-science-and-even-more-data/</link>
		<comments>https://gigaom.com/2014/10/10/this-company-says-it-can-fix-the-sales-process-using-lots-of-data-science-and-even-more-data/#comments</comments>
		<pubDate>Fri, 10 Oct 2014 18:46:25 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[data science]]></category>
		<category><![CDATA[machine learning]]></category>
		<category><![CDATA[neural networks]]></category>
		<category><![CDATA[predictive analytics]]></category>

		<guid isPermaLink="false">http://gigaom.com/?p=880029</guid>
		<description><![CDATA[Provo, Utah–based sales automation company InsideSales has always been interested in applying data analysis to mountains of sales data. After delivering on this mission last year, the company is now ramping&#8230;]]></description>
		<wfw:commentRss>https://gigaom.com/2014/10/10/this-company-says-it-can-fix-the-sales-process-using-lots-of-data-science-and-even-more-data/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Robot startup gets patent for neural networks on GPUs</title>
		<link>https://gigaom.com/2014/02/11/robot-startup-gets-patent-for-neural-networks-on-gpus/</link>
		<comments>https://gigaom.com/2014/02/11/robot-startup-gets-patent-for-neural-networks-on-gpus/#comments</comments>
		<pubDate>Wed, 12 Feb 2014 00:03:34 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[neural networks]]></category>
		<category><![CDATA[Neurala]]></category>

		<guid isPermaLink="false">http://gigaom.com/?p=816026</guid>
		<description><![CDATA[A robotics startup called Neurala has received a patent (No. 8,648,867) for a GPU-based system designed to run artificial neural network models. The patent covers the physical architecture of the system, which&#8230;]]></description>
		<wfw:commentRss>https://gigaom.com/2014/02/11/robot-startup-gets-patent-for-neural-networks-on-gpus/feed/</wfw:commentRss>
		<slash:comments>1</slash:comments>
		</item>
		<item>
		<title>How Google cracked house number identification in Street View</title>
		<link>https://gigaom.com/2014/01/07/how-google-cracked-house-number-identification-in-street-view/</link>
		<comments>https://gigaom.com/2014/01/07/how-google-cracked-house-number-identification-in-street-view/#comments</comments>
		<pubDate>Tue, 07 Jan 2014 23:11:21 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[machine learning]]></category>
		<category><![CDATA[neural networks]]></category>
<category domain="http://search.gigaom.com/stock/"><![CDATA[NSDQ:GOOG]]></category>
		
		<guid isPermaLink="false">http://gigaom.com/?p=790072</guid>
		<description><![CDATA[This post from the MIT Technology Review discusses how Google used deep learning to recognize houses numbers and make Street View more useful (the research paper it cites is here). It's&#8230;]]></description>
		<wfw:commentRss>https://gigaom.com/2014/01/07/how-google-cracked-house-number-identification-in-street-view/feed/</wfw:commentRss>
		<slash:comments>3</slash:comments>
		</item>
		<item>
		<title>Facebook hires NYU deep learning expert to run its new AI lab</title>
		<link>https://gigaom.com/2013/12/09/facebook-hires-nyu-deep-learning-expert-to-run-its-new-ai-lab/</link>
		<comments>https://gigaom.com/2013/12/09/facebook-hires-nyu-deep-learning-expert-to-run-its-new-ai-lab/#comments</comments>
		<pubDate>Mon, 09 Dec 2013 18:38:00 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[data science]]></category>
		<category><![CDATA[image recognition]]></category>
		<category><![CDATA[neural networks]]></category>
<category domain="http://search.gigaom.com/stock/"><![CDATA[NASDAQ:FB]]></category>
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		<guid isPermaLink="false">http://gigaom.com/?p=722394</guid>
		<description><![CDATA[Facebook has hired deep learning expert Yann Lecun from New York University to head up its new artificial intelligence lab. It's part of a bigger push along with -- and against&#8230;]]></description>
		<wfw:commentRss>https://gigaom.com/2013/12/09/facebook-hires-nyu-deep-learning-expert-to-run-its-new-ai-lab/feed/</wfw:commentRss>
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