Continuous Thought Machines: Giving AI a Sense of Time

Modern AI systems sacrifice the crucial property of synchronized neural computation found in biological brains for the sake of efficiency. Researchers introduce the Continuous Thought Machine (CTM), a novel neural network architecture that incorporates neural timing as a foundational element, using a decoupled internal dimension to model the temporal evolution of neural activity. CTM leverages neural synchronization as a latent representation, demonstrating impressive capabilities in tasks such as image classification, maze solving, and parity checks, even building an internal world model for reasoning. Its adaptive computation and interpretability open new avenues for AI research.