Preliminary Schedule Fall 2025
AITU is an open-for-all study group where interested people come together to share insights and discuss recent advancements in AI and general topics within the field of Machine Learning. One of our members always gives an introduction to the topic after which an open discussion follows. We meet in 2A50 (ITU Building) each Tuesday at 4.30 pm over snacks and pizza and finish around 6:30 pm.
This semester we will continue exploring the theoretical and practical foundations of modern machine learning, with a particular focus on reconciling classical ideas with contemporary deep learning practice. We will also look at pressing current issues in AI — from evaluation of Bayesian models to understanding the societal and cognitive costs of generative AI. Finally, we will study some of the most impactful recent methods for adapting and scaling large language models.
Modern Foundations and Evaluation
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W38: Reconciling modern machine learning practice and the bias-variance trade-off
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W39: R-squared for Bayesian regression models
Risks and Adaptation in AI
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W40: The Cognitive Cost of Generative AI: Mapping long-term risks and moderating factors
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W41: LoRA: Low-Rank Adaptation of Large Language Models