Researchers have introduced Neural Computers (NCs), a transformative computing paradigm that merges memory, processing, and input/output into a single learned runtime state. Unlike traditional hardware that executes rigid code, these systems use neural networks to internalize the functions of a running computer. Current prototypes utilize video models to simulate interactive command-line and desktop environments based on user instructions and actions. While these early versions excel at visual rendering and short-term interface control, they still struggle with complex symbolic reasoning and long-term stability. The ultimate vision is the Completely Neural Computer (CNC), a general-purpose machine capable of durable capability reuse and explicit reprogramming. By shifting executable state from external software to the model's own latent dynamics, this approach seeks to move beyond the limitations of current AI agents and world models.