This perspective article connects classical nonlinear dynamics to modern machine learning, arguing that concepts from chaos theory and dynamical systems may inform the development of large-scale generative models. The authors revisit historical works on attractor reconstruction, symbolic dynamics, and complexity-entropy relations, finding parallels with contemporary met...