<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>AI Communication on Aneesh Sathe</title><link>https://aneeshsathe.com/tags/ai-communication/</link><description>Recent content in AI Communication on Aneesh Sathe</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Wed, 23 Jul 2025 05:50:31 +0000</lastBuildDate><atom:link href="https://aneeshsathe.com/tags/ai-communication/index.xml" rel="self" type="application/rss+xml"/><item><title>AI: Explainable Enough</title><link>https://aneeshsathe.com/ai-explainable-enough/</link><pubDate>Wed, 23 Jul 2025 05:50:31 +0000</pubDate><guid>https://aneeshsathe.com/ai-explainable-enough/</guid><description>&lt;p&gt;They look really juicy, she said. I was sitting in a small room with a faint chemical smell, doing one my first customer interviews. There is a sweet spot between going too deep and asserting a position. Good AI has to be just explainable enough to satisfy the user without overwhelming them with information. Luckily, I wasn’t new to the problem.&lt;/p&gt;


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&lt;p&gt;Coming from a microscopy and bio background with a strong inclination towards image analysis I had picked up deep learning as a way to be lazy in lab. Why bother figuring out features of interest when you can have a computer do it for you, was my angle. The issue was that in 2015 no biologist would accept any kind of deep learning analysis and definitely not if you couldn’t explain the details.&lt;/p&gt;</description></item></channel></rss>