#frAIday: Ola Lindberg
#frAIday hybrid
Participate via Zoom or join us at Galaxen, Umeå University, where Professor Ola Lindberg will be present. Welcome!
Abstract
More information to come.
#frAIday: Can AI save a minority language? Meänkieli and digitalization
This talk will outline a Taiga-funded microstudy exploring the technological constraints and challenges surrounding the revitalization of Meänkieli, a minority language spoken in the northern parts of Sweden, particularly in the Tornedalen region. Meänkieli has endured a history of linguistic suppression, including state-enforced prohibitions on its use in schools and public spaces, which disrupted intergenerational transmission and contributed to its marginalization. In recent years, there has been a growing movement to revitalize Meänkieli, with efforts ranging from government language policies to grassroots advocacy by activists and educators. However, despite advancements in AI-driven language technologies, Meänkieli remains critically underrepresented in these systems, hindering its revitalization.
#frAIday Fireside Talk
The aim of this activity is to provide a space for dialogue and discussion on AI from a transdisciplinary perspective. Who is looking for collaboration partners? What are the prerequisites for transdisciplinary AI? What are the examples? Are there any new developments in the field worth sharing? The questions can, but do not need to be, related to the preceding frAIday talk.
#frAIday: Simulating Emotions - as manifestations of Temporal Difference assessment in RL
This talk proposes a Temporal Difference Reinforcement Learning (TDRL) Theory of Emotion, arguing that emotions are manifestations of the brain's reward processing system, specifically its assessment of temporal difference errors. I propose that emotions, ranging from basic joy and distress to more complex feelings like regret and hope, all stem from this fundamental process of evaluating changes in well-being.
#frAIday: AI in biomedicine - from data to drug repurposing
The talk will be focused in presenting how biomedical data can be exploited (from a data-driven and AI perspective) to extract knowledge and insights that allows the creation of drug repurposing hypotheses.
Between hypothesis testing and machine learning in biomedical research
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