https://dasya.itu.dk/tags/ai/ Recent content in AI on DASYA Hugo -- gohugo.io en-us © DASYA, IT University of Copenhagen Mon, 24 Aug 2026 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/current/sbut-gpu-in-space/ Mon, 24 Aug 2026 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/current/sbut-gpu-in-space/ Recently, large datacenters in space have been proposed. See Starcloud, Axiom, Thales Alenia, Google Suncatcher, SpaceX. Aside from the launch cost and many other challenges, one principal question is: How doe s GPU, producing significant amounts of heat, get rid of thermal energy? And even the solar panels, with efficiencies of around 30%, turining 70% of all incoming energy into thermal - how do they? This project should do the calculations as well as build a small demonstrator - a source of thermal energy, potentially a real GPU (we have various small Nvidia EdgeAI devices to burn …), to be deployed in a Mars simulator vacuum tank. https://dasya.itu.dk/for-students/proposals/current/mh-ai-db-workloads/ Fri, 24 Jul 2026 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/current/mh-ai-db-workloads/ BSc Thesis / MSc Thesis. The goal of this project is to use AI coding tools such as ChatGPT Codex and Claude Code together with optimization tools such as OpenEvolve to find innovative solutions for various database-y workloads, including: SIEM workloads, such as finding IP addresses in large security data sets String search workloads, such as finding substrings or evaluating regular expressions in large bodies of text Data analysis workloads, such as executing SQL queries over application logs The core idea is to find better statistics to summarize data partitions. https://dasya.itu.dk/for-students/proposals/current/mh-llm-rng-personas/ Fri, 24 Jul 2026 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/current/mh-llm-rng-personas/ BSc Thesis. This project builds on a previous master’s thesis, Prompting Luck: Bias and Manipulability in LLM-Generated Randomness, that explored replacing traditional random number generators (RNG) in games with large language models (LLMs). The idea is that an LLM can produce “intelligent” random numbers, for example the outcome of a slot machine spin, that take context into account rather than being drawn from a uniform distribution. The goal of this project is to experimentally validate the findings of that thesis by building an actual game, connecting it to an LLM, and putting the idea to the test with real players. https://dasya.itu.dk/for-students/proposals/archive/mh-llm-vs-rng/ Thu, 20 Nov 2025 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/mh-llm-vs-rng/ BSc Thesis / MSc Thesis. The goal of this project is to explore the feasibility and impact of replacing traditional random number generators (RNG) in games with large language models (LLMs). For example, in a slot machine game, the outcome is typically determined by a random number generated each time the “spin” button is pressed. In this project, students will investigate using an LLM to generate these numbers instead. Research questions include: https://dasya.itu.dk/for-students/proposals/current/zk-apachewayang-mcp/ Wed, 28 May 2025 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/current/zk-apachewayang-mcp/ Are you interested in working with a big data open source project and AI? You are welcome to conduct your thesis/project in the context of Apache Wayang. Apache Wayang is the first cross-platform framework that allows users to specify their task/query in a system-agnostic manner and Wayang will determine which is the best system(s) to execute this task with the goal of optimizing performance. For a general overview check this paper.