This visualization demonstrates a probabilistic linking mechanism to construct neural network architecture. Links between nodes are formed with decreasing probability as layers progress deeper, mimicking synaptic pruning in biological neural networks.
Each layer's connectivity follows its own probability distribution, creating a unique but reproducible network topology that balances density and efficiency. Groups represent functional modules or subsystems, while layers represent processing stages. Multiple functional modules can (and often do) co-exist at the same processing stage, so different groups share layers by design to enable parallel, specialized processing within each stage.
Created by: Alix @ HF Labs