===== Privacy-First AI Learning in Your Own Homelab =====
  * **Speaker**: Kevin Howell
  * **Room**: 332
  * **Time**: Saturday, [[https://pretalx.seagl.org/2026/talk/RLWVJU.ics|Oct 24th from 09:00 – 09:50]]  

  * **Format**: Talk (50 minutes)
  * **Difficulty**: Beginner - Moderate
  * **Track**: Technical
  * **Experience**: Principal Software Engineer at Red Hat with over 15 years of industry experience, currently driving technical direction for Red Hat OpenShift AI.  

==== Description: ====  
Many convenient and cheap ways to learn about AI come with a significant catch: free AI services often use your data to train their models, creating a privacy nightmare. Instead of relying on proprietary providers, you can use open-source software and open weight models to learn AI concepts while maintaining complete privacy. This talk provides a lightning-fast tour of open source projects for home AI engineering, focusing on inference with small models, image generation and recognition, and basic observability.

**Target Audience:**  
  * Self-hosters 
  * Enthusiasts