Metamaterials, renowned for their exceptional mechanical, electromagnetic, and thermal properties, hold transformative potential across diverse applications, yet their design remains constrained by labor - intensive trial - and - error methods and limited data interoperability. Here, we introduce CrossMatAgent -- a novel multi - agent framework that synergistically integrates large language models with state - of - the - art generative AI to revolutionize metamaterial design. By orchestrating a hierarchical team of agents -- e ach specializing in tasks such as pattern analysis, architectural synthesis, prompt engineering, and supervisory feedback -- our system leverages the multimodal reasoning of GPT - 4o alongside the generative precision of DALL - E 3 and a fine - tuned Stable Diffusion Extra Large ( XL) model. This integrated approach automates data augmentation, enhances design fidelity, and produces simulation - and 3D printing - ready metamaterial patterns. Comprehensive evaluations, including Contrastive Language - Image Pre - training ( C LIP) - based alignment, SHAP ( SHapley Additive exPlanations) interpretability analyses, and mechanical simulations under varied load conditions, demonstrate the framework's ability to generate diverse, reproducible, and application - ready designs . CrossMatAgent thus establishes a scalable, AI - driven paradigm that bridges the gap between conceptual innovation and practical realization, paving the way for accelerated metamaterial development.

Artificial General Intelligence (AGI), possessing the capacity to comprehend, learn, and execute tasks with human cognitive abilities, engenders significant anticipation and intrigue across scientific, commercial, and societal arenas. This fascination extends particularly to the Internet of Things (IoT), a landscape characterized by the interconnection of countless devices, sensors, and systems, collectively gathering and sharing data to enable intelligent decision-making and automation. This research embarks on an exploration of the opportunities and challenges towards achieving AGI in the context of the IoT. Specifically, it starts by outlining the fundamental principles of IoT and the critical role of Artificial Intelligence (AI) in IoT systems. Subsequently, it delves into AGI fundamentals, culminating in the formulation of a conceptual framework for AGI's seamless integration within IoT. The application spectrum for AGI-infused IoT is broad, encompassing domains ranging from smart grids, residential environments, manufacturing, and transportation to environmental monitoring, agriculture, healthcare, and education. However, adapting AGI to resource-constrained IoT settings necessitates dedicated research efforts. Furthermore, the paper addresses constraints imposed by limited computing resources, intricacies associated with large-scale IoT communication, as well as the critical concerns pertaining to security and privacy.