<?xml version="1.0" encoding="utf-8"?>
<?xml-stylesheet type="text/xsl" href="../assets/xml/rss.xsl" media="all"?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Dzu's Blog (Posts about ai)</title><link>https://blog.lazy-evaluation.net/</link><description></description><atom:link href="https://blog.lazy-evaluation.net/categories/ai.xml" rel="self" type="application/rss+xml"></atom:link><language>en</language><copyright>Contents © 2026 &lt;a href="mailto:dzu@member.fsf.org"&gt;Detlev Zundel&lt;/a&gt; </copyright><lastBuildDate>Fri, 27 Mar 2026 11:42:19 GMT</lastBuildDate><generator>Nikola (getnikola.com)</generator><docs>http://blogs.law.harvard.edu/tech/rss</docs><item><title>Small Notes on Machine Learning</title><link>https://blog.lazy-evaluation.net/posts/notes_on_machine_learning.html?pk_campaign=feed</link><dc:creator>Detlev Zundel</dc:creator><description>&lt;div&gt;&lt;p&gt;So Machine Learning has become one of the hottest topics of today.
Programs in the domain of "Convolutional Neural Networks" (CNN)
capable of recognizing cats in images are described in an awe-struck
tone as a form of "Artificial Intelligence" even though they are
essentially simple operations on a massive scale yielding candidates
sorted by probability.  It is of course difficult not to be captured
by the hype, but I still think it is worthwhile remembering some of
the problems that are already known at this time.&lt;/p&gt;
&lt;img alt="Convolutional Neural Network" class="align-center" src="https://blog.lazy-evaluation.net/images/ConvnetDiagram.png" style="width: 300px;"&gt;
&lt;p&gt;&lt;a href="https://blog.lazy-evaluation.net/posts/notes_on_machine_learning.html?pk_campaign=feed"&gt;Read more…&lt;/a&gt; (5 min remaining to read)&lt;/p&gt;&lt;/div&gt;</description><category>ai</category><category>cnn</category><category>ml</category><guid>https://blog.lazy-evaluation.net/posts/notes_on_machine_learning.html</guid><pubDate>Mon, 01 Apr 2019 17:57:48 GMT</pubDate></item></channel></rss>