Looking forward, the path from narrow AI to more general forms of intelligence will likely not be a single architectural breakthrough but a convergence of multiple lines of inquiry. Progress in representation learning, structured reasoning, embodiment, continual adaptation, and value alignment may gradually dissolve the boundaries that currently constrain artificial systems. The history of AI is replete with predictions of imminent human-level intelligence that proved premature. Caution is warranted, but so is recognition of the genuine advances that have occurred. Each generation of technology expands the space of possible applications while revealing new layers of complexity in the problem of intelligence itself. The careful integration of empirical discovery with theoretical understanding remains the surest guide through this evolving landscape, where the deepest questions are as much about human purpose as they are about machine capability.