Arrive with a laptop; leave with a tiny, repeatable AI workflow.

In this hands-on session, you’ll try OpenCLIP visual search on a provided demo image set (no uploads) to understand how vector search works, then run LLM experiments to clean a messy OCR page, extract people/places/dates/subjects, and export CSV/JSON. We’ll keep humans in the loop (simple review gates and fallback rules), talk costs, privacy, and sustainability, and end with a 90-day mini-roadmap for your own collection.

Everything is browser-only and beginner-friendly; optional power-user prompts are available for those who want to go deeper.

Level of experience: none required / beginner (intermediate welcome)

Detailed timetable (120 min):

• 00–10: Primer (what gen-AI is/isn’t; goals)
  

• 10–25: OpenCLIP demo—vector search basics; try queries on a hosted set
  

• 25–55: LLM transcript clean-up (before/after)
  

• 55–85: Metadata extraction → JSON → CSV (quick validation)
  

• 85–100: Group debrief (errors, ethics, trust)
  

• 100–115: From demo to pipeline: review gates, fallback rules, rough cost notes
  

• 115–120: Roadmap sprint: next steps & support needs
  

Technical requirements:

• Laptop + modern browser; conference Wi-Fi
  

• Free ChatGPT or Gemini account helpful; pairing/observer mode for those who can’t sign up
  

• No installs / no USB; all tasks are browser-based
  

• Sample data (image set + OCR page) provided by instructor