Modular Architecture

Modular architecture in artificial intelligence and related fields focuses on designing systems composed of independent, reusable components, aiming for improved scalability, interpretability, and efficiency. Current research explores this concept across diverse applications, including language models (using transformer-based circuits), reinforcement learning (via assume-guarantee paradigms and modular software architectures), and large-scale scientific workflows (e.g., science factories). This approach offers significant advantages by enabling easier adaptation to new tasks, facilitating the analysis of individual components, and potentially leading to more robust and efficient systems across various domains.