Intro + 2–3 talks

PyCarinthia #1 – hello_world

Wednesday, 14 October 2026 17:30 Vienna time Omansaal, University of Klagenfurt
This meetup has taken place. Read the recap with talk summaries, slides, and photos →

The first PyCarinthia meetup. The goal is simple: meet the people in Carinthia who build with Python and AI, and shape the community together.

The evening opens with a short intro to what PyCarinthia is and what it can become, followed by two to three talks on Python, AI, and everything around them. Afterwards there is open discussion and drinks. Details on the exact schedule will follow.

Speakers

Christian Klimbacher: When AI Calls a Multimeter for Help, You Get More Than Expected

Speaker card for Christian Klimbacher

Given nothing but a photo of an unknown circuit board, can we work out what is on it? This talk walks through a Python system that loops over imperfect sources: a vision LLM reads the board, datasheets supply expectations, and a simple multimeter measures in-circuit, where parallel paths make any single reading unclear. Each source only knows part of the answer, but together they find values that were unknown before. Live measurement on stage included.

Benjamin Hackl: Musings from Maintaining Manim

Speaker card for Benjamin Hackl

Manim is a Python library for creating mathematical animations, originally built by popular math communicator Grant “3Blue1Brown” Sanderson. After a quick interactive demo, I’ll talk about my path into open source and explain why my car mechanic is responsible both for me being rude to people on the internet and for me occasionally getting to press the “new Manim release” button. On a more serious note, I will share some thoughts about community building and dealing with AI slop in the age of the clankers.

Alina Nessel: LiveSaferOverview: Saving Lives in Tunnels with AI

Speaker card for Alina Nessel

When an accident happens in a highway tunnel, rescue teams face a major challenge: keeping a clear overview of the situation. LiveSaferOverview uses Artificial Intelligence to solve this problem. I trained the AI with 80,000 images so it can automatically track emergency vehicles using normal tunnel cameras. It then shows their exact positions on a digital, real-time map on a smartphone. This clear overview prevents rescue teams from driving to the wrong location. By saving these critical minutes, the AI helps to save lives.

Good to know

Just here to listen? Perfect. Come along, ask questions, or simply see who else is around.

RSVPs run through our Meetup group. This page stays the canonical record of the event, so the details here hold even if Meetup does not.

Python, AI, data, web, automation, open source, research, hobby projects - all of it is welcome. The only prerequisite is curiosity.

This kickoff is kindly supported by the FTF (Förderverein Technische Fakultät).