<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Mia on Aayush Bajaj's Augmenting Infrastructure</title><link>https://abaj.ai/tags/mia/</link><description>Recent content in Mia on Aayush Bajaj's Augmenting Infrastructure</description><generator>Hugo</generator><language>en</language><copyright>© 2026 Aayush Bajaj</copyright><lastBuildDate>Sun, 19 Jul 2026 04:36:28 +1000</lastBuildDate><atom:link href="https://abaj.ai/tags/mia/index.xml" rel="self" type="application/rss+xml"/><item><title>The Bayesian Cat</title><link>https://abaj.ai/blog/the-bayesian-cat/</link><pubDate>Sun, 08 Dec 2024 18:39:13 +1100</pubDate><guid>https://abaj.ai/blog/the-bayesian-cat/</guid><description>&lt;p>This blog post has been created to convince you that real-world
probability, is in fact &lt;span class="underline">Bayesian&lt;/span> probability.&lt;/p>
&lt;p>Anyone who believes that a frequentist approach is superior may be
correct (for that particular example), but it must be said that the
Bayesian framework is a superset of this naive and trivial
card-playing model of probability.&lt;/p>
&lt;p>We are no longer trying to determine the probability of landing a
&lt;code>double-six&lt;/code> dice roll, and rather we are trying to figure out what
the probability is that Mia (our cat) will be waiting for us on the
porch when we get home.&lt;/p></description></item></channel></rss>