Researchers are fundamentally rethinking artificial intelligence by drawing inspiration directly from the architecture of the human brain. Weifeng Liu from Vista Zenith, alongside colleagues, proposes a novel neural network paradigm , Brain-like Neural Networks (BNNs) , that moves beyond manually designed structures and embraces autonomous evolution. This work is significant because it presents LuminaNet, the first instantiation of a BNN capable of dynamically modifying its own architecture without relying on traditional convolutions or self-attention mechanisms. Extensive experiments reveal LuminaNet achieves substantial performance gains on image classification (CIFAR-10) and text generation (TinyStories), exceeding established models like LeNet-5, AlexNet, MLP-Mixer,…