<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>hershel</author><text>Singluar computing have built a chip based on this tech, and deployed in a military UAV. It enabled tracking of objects(which ws impossible before due to power constraints), at 6400x the performance&amp;#x2F;power of other best known methods.&lt;p&gt;&lt;a href=&quot;http://www.defensetechbriefs.com/component/content/article/17021&quot; rel=&quot;nofollow&quot;&gt;http:&amp;#x2F;&amp;#x2F;www.defensetechbriefs.com&amp;#x2F;component&amp;#x2F;content&amp;#x2F;article&amp;#x2F;1...&lt;/a&gt;&lt;p&gt;&lt;a href=&quot;http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1693583&quot; rel=&quot;nofollow&quot;&gt;http:&amp;#x2F;&amp;#x2F;proceedings.spiedigitallibrary.org&amp;#x2F;proceeding.aspx?ar...&lt;/a&gt;&lt;p&gt;From the paper:
&amp;quot;The hardware is designed to perform high dynamic range arithmetic with roughly 1% error per operation. Singular has
developed and studied varied algorithms for producing high quality results despite the approximate hardware. These
studies use a perfect simulation of the accelerator’s arithmetic. Tasks that have been explored include summing
thousands of numbers without accumulating error, k-nearest neighbor classification (KNN), foreground&amp;#x2F;background
separation using Gaussian mixture models, iterative reconstruction tomography, deblurring using the Richardson-Lucy
deconvolution algorithm, FFTs, radar processing, neural net learning, and other tasks. Most of these algorithms need
slight adaptations to prevent cumulative effects of the 1% 
error, but with those adaptations all perform as desired.&amp;quot;</text><parent_chain></parent_chain></comment><story><title>Computing 10,000X more efficiently (2010) [pdf]</title><url>http://web.media.mit.edu/~bates/Summary_files/BatesTalk.pdf</url></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>valarauca1</author><text>This topic was already discussed albeit satirically in another publication. Namely the, &amp;quot;The Slow Winter.&amp;quot;[1] Which while comedic makes good points about hardware architecture.&lt;p&gt;[1] &lt;a href=&quot;https://www.usenix.org/system/files/1309_14-17_mickens.pdf&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;www.usenix.org&amp;#x2F;system&amp;#x2F;files&amp;#x2F;1309_14-17_mickens.pdf&lt;/a&gt;</text><parent_chain></parent_chain></comment><story><title>Computing 10,000X more efficiently (2010) [pdf]</title><url>http://web.media.mit.edu/~bates/Summary_files/BatesTalk.pdf</url></story>