aiqbench analysis

This research demonstrates that artificial neural networks can autonomously construct their own learning architectures without explicit designer intervention, a capability crucial for assessing biological plausibility. By allowing randomly connected units to self-organize into effective information-processing systems, the study bridges the gap between engineered AI and the brain's natural reorganization mechanisms. The findings suggest that future models prioritizing self-organization may offer deeper insights into neural plasticity than current high-performance but manually tuned algorithms.