Researchers Simon et al. challenge the prevailing pessimism regarding the theoretical foundations of neural networks. The paper argues that a formal scientific theory of deep learning is inevitable. This perspective counters the current trend where both practitioners and AI safety researchers view the internal mechanics of models as fundamentally opaque.