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	<title>Comments on: Sifting through a trillion electrons</title>
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	<link>http://www.kurzweilai.net/sifting-through-a-trillion-electrons</link>
	<description>Accelerating Intelligence</description>
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		<title>By: Jonathan Cole</title>
		<link>http://www.kurzweilai.net/sifting-through-a-trillion-electrons/comment-page-1#comment-21822</link>
		<dc:creator>Jonathan Cole</dc:creator>
		<pubDate>Fri, 29 Jun 2012 20:50:55 +0000</pubDate>
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		<description>God uses this kind of algorithm to determine the most interesting beings to be aware of. How would we know if we made the cut?</description>
		<content:encoded><![CDATA[<p>God uses this kind of algorithm to determine the most interesting beings to be aware of. How would we know if we made the cut?</p>
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		<title>By: Bri</title>
		<link>http://www.kurzweilai.net/sifting-through-a-trillion-electrons/comment-page-1#comment-21674</link>
		<dc:creator>Bri</dc:creator>
		<pubDate>Fri, 29 Jun 2012 10:52:21 +0000</pubDate>
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		<description>This type of data manipulation is essential for many important daily created data sets. Just think of it in relation to Goggle, or financial models , health care researcher, genomic research, or my favorite, a Watsonesq personal program. I think neuromorphic chips should excel at these tasks, because they can reconfigure on their own, to solve tasks. So when they say in the article that the key was to break the problem down into subsets, neuromorphic chips could alter the structure of the code in response to problem solving needs. As they said in that article, a single neuron became sensitive to a single visual component. It should be able to find hidden patterns in massive data sets with relative ease.</description>
		<content:encoded><![CDATA[<p>This type of data manipulation is essential for many important daily created data sets. Just think of it in relation to Goggle, or financial models , health care researcher, genomic research, or my favorite, a Watsonesq personal program. I think neuromorphic chips should excel at these tasks, because they can reconfigure on their own, to solve tasks. So when they say in the article that the key was to break the problem down into subsets, neuromorphic chips could alter the structure of the code in response to problem solving needs. As they said in that article, a single neuron became sensitive to a single visual component. It should be able to find hidden patterns in massive data sets with relative ease.</p>
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		<title>By: Ken</title>
		<link>http://www.kurzweilai.net/sifting-through-a-trillion-electrons/comment-page-1#comment-21632</link>
		<dc:creator>Ken</dc:creator>
		<pubDate>Fri, 29 Jun 2012 06:56:13 +0000</pubDate>
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		<description>Amazing news. Thanks for posting.</description>
		<content:encoded><![CDATA[<p>Amazing news. Thanks for posting.</p>
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