My name is Christoph Pröschel, berlin-based full-stack engineer.
Currently:
🌍 Building AI-powered material visibility at visia.ai.
Highlights:
🚀 Co-Founder of weview.tv (Techstars ‘18, exited ‘19)
👨💻 Contributing to open source
🧑🎓 Msc @ TU Berlin. Thesis: Multi-Agent Reinforcement Learning for Dynamic Climate Policy Games link
Python monorepo with uv and pex
With the current hype in AI it has become quite hard to avoid writing python and shipping it at scale. Unfortunately, the python packaging and environment system is so notoriously convoluted that there is even an infamous xkcd comic about it. Enter uv, the rising star of the python community that has succeeded in solving all these problems while also being significantly more performant. But while uv is great at managing your python environment it does not yet have a clear answer for how to bundle and ship them....
Master Thesis: Multi-Agent Reinforcement Learning for Dynamic Climate Policy Games
View the full thesis here. Abstract Despite concerted efforts by researchers and policymakers, governments are failing to implement the global coordination needed to implement policies that could avert the disaster of unmitigated climate change. Existing economic models are often ill-equipped to capture the complexities of dynamic, strategic interactions among multiple agents. The research on international mechanisms such as climate clubs, for instance, is often limited to one-shot games due to the combinatorial explosion of sequential negotiation steps....
Lab Grown Meat Is Not a Climate Solution
Few topics spark as much controversy in the climate debate as the assertion that we need to cut our meat consumption if we want to reach our climate targets. On some primal level going for the burger on your plate is a much more outrageous act than going for your car. So it’s no surprise that technical-minded people have been looking for a panacea in the form of lab-grown meat. And the pitch is alluring: If the plan works out the burger is safe and we get to reduce our emissions....
Viper Paper Implementation
In this article I talk about the implementation of the paper “Verifiable Reinforcement Learning via Policy Extraction” by Osbert Bastani et al.
Rasa L3 presentation: Supercharging Conversational AI with Human Agent Feedback Loops
Here I talk about how to get the most out of your conversational AI and customer support by having your AI suggest likely responses and then training it on the selection that customer support makes. Links: Talk: https://www.youtube.com/watch?v=MCXumfwcmXE Implementation Blog post: How to level up your customer support and AI using Airy and Rasa X