Can Images Classify Themselves? | Self-Organization and Neural Cellular Automata

The video explores the use of salamanders as models for machine learning, focusing on their self-repair abilities. It introduces cellular automata, explaining their rules and the concept of neural cellular automata, which combine neural networks with traditional automata. The video discusses training these models to stabilize and repair images, addressing challenges like instability and self-classification. Techniques to improve model performance, such as altering loss functions and handling missing data, are also covered.

What challenges arise when training a model to generate a target image?

How does the model handle missing pieces in an image during regeneration?

What adjustments are made to the loss function to improve the model's performance?