My name is Balázs, but everyone just calls me Balu. I am a Master Student in Statistics at ETH Zurich, interested broadly in Data Science, Machine Learning and AI, with a particular focus on Reinforcement Learning and Large Language Models.

The incredible odyssey I am about to tell you about all started one day back in the spring of 2025, when I saw on the Instagram story of ETH that UNDRR (United Nations Office for Disaster and Risk Reduction) was looking for Data Science and AI Interns in Bangkok. I immediately knew that I had to apply. While traveling around in Southeast Asia for two months two years ago, I fell in love with Asian culture. Considering that in my studies I put a strong focus on Data Science and AI, I thought this is the perfect opportunity for me!

Fast forward 6 months, I am standing at the gates of ESCAP (Economic and Social Commission for Asia and the Pacific) in Bangkok, ready to be picked up and start my internship. I quickly got to know my team and all the other interns. I was surprised to see how many other interns there were across all the UN agencies in Bangkok. This made it very easy to find friends and build a social circle right from the beginning. What I valued right from the getgo, was the diverse background of all the people around me, be it culturally or academically. Most of the other interns were in the same phase of life as me, hovering somewhere around finishing their Master’s Degree. The majority had a background in social sciences, such as economics or law. At ETH we sometimes forget that there is also a world out there that does not care about math as much we do! It was very nice to be surrounded by people that look at the world from another angle compared to most STEM students. This helped me broaden my horizons in many aspects of life.

The start of my internship was fairly slow. Because the other two interns (Bilal, also an applied maths student from ETH, and Siwei, studying in Stockholm) and I were the first three AI interns ever at UNDRR, it was a lot of figuring out on both ends. As per usual, the first few weeks I was busy clicking through all the online onboardings. Who knew that as an intern in the IT team, I needed to know how to behave in case I am trapped in a mine field in the desert. But I soon got introduced to my main project: DATUM, UNDRRs RAG-based LLM. In a nutshell, this is a language model like ChatGPT, that builds on internal data at UNDRR. The language model can retrieve information from documents from the database of UNDRR that is relevant for the question a user may ask.

To my big surprise, after some weeks I was named the Project Manager. It felt quite surreal being given this responsibility as an intern. But I quickly realised that this internship would not be like any other internship. I doubt that there are many other internships that give you the same amount of responsibility right from the start as we have been given. This was both, challenging and also rewarding, at the same time. Considering the fact that AI was not the main focus of our team and something most members were not deeply familiar with, we interns were the ones with the most expertise and hence we were the ones who built the foundation for future interns or even full time employees. This is one of the things that I am most proud of: setting something in motion that will hopefully live on way beyond the end of my internship. To educate the other members of our team on topics revolving around AI, we held bi-weekly AI-talks, where we interns gave presentations about AI-related topics that we deemed interesting and relevant.

One of my proudest moments was when Jeanette Elsworth (Chief of the Communication, Advocacy and Knowledge Management Section of UNDRR) came to visit us in Bangkok and I had the opportunity to present to her the progress of our work. Within the three to four months that I have been there at that point, we had a prototype running of our RAG-based LLM. It was really rewarding to see the engagement and excitement of the whole team. For the remaining part of my internship, we further improved our model and developed an interface for it for internal use.

Another thing that I appreciated and made use of, was, that I could attend most of the conferences held at ESCAP. One of these conferences was the “AI for Developing Countries Forum” (https://af.net/bangkok/). By attending this conference, I learned a lot about the human aspect of artificial intelligence, and the imbalance in power in the AI race that is ongoing worldwide. The two most striking learnings for me were:

1) 60% of web content is written in English, whereas only around 16% of the world population speaks English (https://pollicy.medium.com/the-digital-divide-extends-to-language-what-now-919da821389e). This leads to an immense bias towards the English language when training LLMs on all of the data available on the web.

2) The CLOUD Act: a law that allows American federal law enforcement agencies to access data stored on servers from US-based tech companies (Meta, Google, Amazon, etc.) regardless of the location of the datacenter, be it in the US or abroad (https://en.wikipedia.org/wiki/CLOUD_Act, https://www.congress.gov/bill/115th-congress/house-bill/4943, https://www.govinfo.gov/content/pkg/PLAW-115publ141/pdf/PLAW-115publ141.pdf). Learning about this law made me question all the privacy claims that these big tech giants make. Attending this conference really broadened my horizons and gave me a new perspective on AI and data sovereignty. 

Outside of work, I had the opportunity to make Bangkok, the concrete jungle of Thailand, my home and engage in all the craziness and chaos it has to offer. I also had the privilege to travel around the country and explore it’s beautiful beaches, its underwater world while scuba diving, its majestic temples and most importantly, get to know the immense kindness of the Thai people. Many weekends and long evenings well spent that I will keep in good memory for the rest of my life.

At this point, I want to say a big thank you to all the people that have made this experience so amazing and unforgettable. Some people I want to mention explicitly include my direct supervisors, Anders Hansen and Revati Mani, my coworkers with whom I worked together on DATUM: Ryan Sandigan, Bilal Bounajma and Siwei Zhang and Camilla Andreozzi; and all the other interns that I’ve met along the way.

Lastly, none of this would have been possible without the support of ETH Studios. I am immensely grateful to have been given the financial support necessary to embark on this once in a lifetime opportunity.