From Neurons to Transformers: Cognitive Principles in AI Research
Module Description
| Course | Module Abbreviation | Credit Points |
|---|---|---|
| BA-2010[100%|75%] | CS-CL | 6 LP |
| BA-2010[50%] | BS-CL | 6 LP |
| BA-2010[25%] | BS-AC | 4 LP |
| BA-2010 | AS-CL | 8 LP |
| Master | SS-CL-TAC | 8 LP |
| Lecturer | Jan Mackensen |
| Module Type | Proseminar / Hauptseminar |
| Language | English |
| First Session | 13.04.2026 |
| Time and Place | Mo, 13:15 - 14:45, SR 10 / INF 346 |
| Commitment Period | tbd. |
Participants
All advanced CL Bachelor students and all CL master students. Students from MSc Data and Computer Science or MSc Scientific Computing with Field of Application Computational Linguistics are welcome after getting permission from the lecturer. MSc Scientific Computing students can only take the course as HS for 8 LP. If the seminar should be oversubscribed, CL students will have priority.
Prerequisites for Participation
- Statistical Methods for Computational Linguistics
- Introduction to Neural Networks
Assessment
- Presentation
- Project
Content
The development of the Transformer architecture and its impressive performance gains in a wide range of tasks demonstrate the potential of integrating human cognitive processes, such as attention, into AI architectures. In general, many concepts of modern AI are based on observations and findings from research into human intelligence. For instance, multi-layer perceptrons are loosely modelled on neural structures in the brain, and key properties of convolutional neural networks can be found in a similar form in the visual cortex.
This course aims to examine such concepts from neuroscience, psychology, cognitive science and early AI research, critically evaluating their influence on current AI development. Secondly, it will explore key research topics from these disciplines that have been developed in the past and could potentially play an important role in AI research in the future.
