<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
			xmlns:itunes="http://www.itunes.com/dtds/podcast-1.0.dtd"
		>

<channel>
	<title>Gigaom Search &#187; People &#187; Chris Wiggins</title>
	<atom:link href="http://search.gigaom.com/person/chris-wiggins/feed/" rel="self" type="application/rss+xml" />
	<link>http://search.gigaom.com</link>
	<description>Search and browse the archives</description>
	<lastBuildDate>Wed, 11 Mar 2015 13:08:37 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>hourly</sy:updatePeriod>
	<sy:updateFrequency>1</sy:updateFrequency>
	<generator>http://wordpress.org/?v=4.1</generator>
	<item>
		<title>The New York Times is looking to machine learning to help it understand reader behavior</title>
		<link>https://gigaom.com/2014/06/19/the-new-york-times-is-looking-to-machine-learning-to-help-it-understand-reader-behavior/</link>
		<comments>https://gigaom.com/2014/06/19/the-new-york-times-is-looking-to-machine-learning-to-help-it-understand-reader-behavior/#comments</comments>
		<pubDate>Thu, 19 Jun 2014 21:03:13 +0000</pubDate>
		<dc:creator><![CDATA[Mathew Ingram]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Media]]></category>
		<category><![CDATA[structure2014]]></category>
<category domain="http://search.gigaom.com/stock/"><![CDATA[NYSE:NYT]]></category>
		
		<guid isPermaLink="false">http://gigaom.com/?p=851905</guid>
		<description><![CDATA[Chris Wiggins, a theoretical physicist and mathematician who is the chief data scientist for the New York Times, says he is trying to help the paper detect patterns in the data&#8230;]]></description>
		<wfw:commentRss>https://gigaom.com/2014/06/19/the-new-york-times-is-looking-to-machine-learning-to-help-it-understand-reader-behavior/feed/</wfw:commentRss>
		<slash:comments>3</slash:comments>
		</item>
		<item>
		<title>You can teach an old dog new tricks: machine learning at a 163-year old company</title>
		<link>http://events.gigaom.com/structure-2014/session/you-can-teach-an-old-dog-new-tricks-machine-learning-at-a-163-year-old-company/</link>
		<comments>http://events.gigaom.com/structure-2014/session/you-can-teach-an-old-dog-new-tricks-machine-learning-at-a-163-year-old-company/#comments</comments>
		<pubDate>Thu, 19 Jun 2014 08:48:02 +0000</pubDate>
		<dc:creator><![CDATA[stacey]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Structure]]></category>
		<category><![CDATA[Structure 2014]]></category>

		<guid isPermaLink="false">http://events.gigaom.com/structure-2014/session/tba-9/</guid>
		<description><![CDATA[Like every other industry that is being disrupted by the internet, media companies are finding it increasingly important to work with and understand the data behind their business, and the New&#8230;]]></description>
		<wfw:commentRss>http://events.gigaom.com/structure-2014/session/you-can-teach-an-old-dog-new-tricks-machine-learning-at-a-163-year-old-company/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
	</channel>
</rss>
