Episode

Use Case Thursday: Should You Host Your Own AI Model?

Podcast
Generative AI 101
Published
Aug 6, 2026
Duration seconds
826
Processing state
not_requested
Canonical source
https://generativeai101.podbean.com/e/use-case-thursday-should-you-host-your-own-ai-model/
Audio
https://mcdn.podbean.com/mf/web/h4kpy5zjptdc6dv6/UseCaseThursday080626.mp3
JSON
/v1/public/podcasts/generative-ai-101-6932184/episodes/use-case-thursday-should-you-host-your-own-ai-model
Markdown
/podcast/generative-ai-101-6932184/use-case-thursday-should-you-host-your-own-ai-model.md

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Summary

Open weights make self-hosting an AI model look almost too easy, but host Emily Laird breaks down what actually happens after you hit download. This episode walks through the infrastructure, staffing, security and compliance costs that separate a slick demo from a real institutional service, including GPU power draws, KV cache limits and FERPA obligations. It's a reality check on when owning your own model actually saves money, and when it just means insourcing a cloud provider without the cloud provider's scale. If you've ever heard someone ask "why are we paying Microsoft," this episode answers it. 🎯 JOIN THE AI WEEKLY MEETUPS https://www.uwstout.edu/ai-weekly-meetup 📩 EMAIL REMINDERS FOR THE MEETUPS https://app.e2ma.net/app2/audience/signup/2101263/1779703/ 💬 CONNECT WITH EMILY LAIRD ON LINKEDIN http://www.linkedin.com/in/meet-emily-laird