


Mathematical brain modeling
This lecture overviews Mathematical Brain Modeling that has many applications in Artificial Neural Networks. It covers the following topics in detail: Brain Cells (Sensory and Motor neurons, Interneurons, glia).



Large Language Models, ChatGPT and University Education
This lecture overviews the impact of the Large Language Models, particularly of ChatGPT language model in Education, e.g., in Universities. First it present the ChatGPT transformer structure and ChatGPT training.



Gray Box Optimization
In Gray Box Optimization, the optimizer is given access to the set of M subfunctions. We prove Gray Box Optimization can efficiently compute hyperplane averages to solve non-deceptive problems in time.
Domain Adaptation and Generalization
There is an issue of domain shift in machine learning models, which occurs when models trained on one dataset perform poorly when tested on data from a different source.



Real-World Learning
In the past decade, artificial intelligence has made remarkable progress, achieving feats like self-driving cars, defeating go-masters, and precise image categorisation through supervised deep learning with labelled data.
Robots Learning (Through) Interactions
The acquisition and self-improvement of novel motor skills is among the most important problems in robotics.