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	<title>Comments on: Artificial Intelligence  vs Social Intelligence</title>
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	<link>http://ibiblio.org/pjones/blog/artificial-intelligence-vs-social-intelligence/</link>
	<description>Accept no substitutes</description>
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		<title>By: Ian Parker</title>
		<link>http://ibiblio.org/pjones/blog/artificial-intelligence-vs-social-intelligence/comment-page-1/#comment-51277</link>
		<dc:creator>Ian Parker</dc:creator>
		<pubDate>Sat, 28 Oct 2006 10:23:49 +0000</pubDate>
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		<description>I am a little bit more optimisic. The basis of searching is to get the meaning of words correct. In other words we have to translate into a concet language. Looking at Google we can see tthat we are a long way from this.

&quot;El barco attravesto una cerradura.&quot;
and &quot;La estacion de ressorte&quot; I did not know stations had elasticity.

There are however a number of techniques which will show considerable promise. If we employ LSA (Latent Semantic Analysis) which is basically Principlal Component Analysis applied to text we obtain word probabilities. A neccessary (and sufficient) condition for good translation is simply that &quot;éclusia&quot; comes above &quot;cerradura&quot; in terms of probability and that &quot;primavera&quot; comes top of the possibilities for &quot;spring&quot;.

This problem is a key one in AI. VoIP is at the point where individual phonemes are analized as well if not better than human listeners. Why is VoIP so bad. Let us look at the translation paradyme again. Suppose we have order &quot;calallero&quot; and &quot;noche&quot; we may use LSA to do it, both words &quot;(k)night&quot; sound the same in English.

This problem, as we can see, is a central one. The same solution appertains for translation, speech and retrieval. The problem is that LSA demands a matrix multiplication to find every word and spiders will need to operate on multicored servers.</description>
		<content:encoded><![CDATA[<p>I am a little bit more optimisic. The basis of searching is to get the meaning of words correct. In other words we have to translate into a concet language. Looking at Google we can see tthat we are a long way from this.</p>
<p>&#8220;El barco attravesto una cerradura.&#8221;<br />
and &#8220;La estacion de ressorte&#8221; I did not know stations had elasticity.</p>
<p>There are however a number of techniques which will show considerable promise. If we employ LSA (Latent Semantic Analysis) which is basically Principlal Component Analysis applied to text we obtain word probabilities. A neccessary (and sufficient) condition for good translation is simply that &#8220;éclusia&#8221; comes above &#8220;cerradura&#8221; in terms of probability and that &#8220;primavera&#8221; comes top of the possibilities for &#8220;spring&#8221;.</p>
<p>This problem is a key one in AI. VoIP is at the point where individual phonemes are analized as well if not better than human listeners. Why is VoIP so bad. Let us look at the translation paradyme again. Suppose we have order &#8220;calallero&#8221; and &#8220;noche&#8221; we may use LSA to do it, both words &#8220;(k)night&#8221; sound the same in English.</p>
<p>This problem, as we can see, is a central one. The same solution appertains for translation, speech and retrieval. The problem is that LSA demands a matrix multiplication to find every word and spiders will need to operate on multicored servers.</p>
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