Current dominant artificial intelligence, powered by neural network-based foundation models, presents a profound challenge to traditional conceptions of human uniqueness— particularly in intelligence and creativity. This keynote argues that biological and artificial neural networks constitute two complex connectionist systems that share deep analogies—in architecture, learning dynamics, and emergent behavior—while also exhibiting fundamental differences in substrate, embodiment, and developmental trajectory. Drawing on neuroscience, cognitive psychology, and connectionist theory, we examine how biological creativity emerges from the dynamic interplay between the Default Mode Network and the Executive Control Network—a dual-process architecture of spontaneous ideation and deliberate evaluation—and trace compelling structural and functional parallels with artificial neural network architectures. Crucially, we are witnessing a paradigm shift: AI is escaping the era of learning exclusively from human-generated data and entering an era of experience. Reinforcement learning techniques are enabling AI systems to explore their own paths in reasoning, creativity, and scientific discovery—moving from small-c creativity toward domain-level Big C achievements. This shift is compounded by recursive self-improvement: AI systems that optimize their own architectures and capabilities, raising fundamental questions about the trajectory, controllability, and societal consequences of intelligence that improves itself at accelerating rates. Meanwhile, the gap between the exponential evolution of AI and its real impact on society is widening. This asymmetry creates extraordinary opportunities but also an urgent imperative: AI literacy is becoming compulsory. Without it, society risks losing its ability to make informed collective decisions about a technology that will reshape every domain of human activity. Understanding both forms of intelligence—their mechanisms, their parallels, their creative potential, and their limitations—is not an academic exercise. It is an existential imperative for ensuring that the next wave of intelligent systems serves human dignity, creativity, and collective progress.