A key differentiator from early research is that Cassie was developed to be emotionally responsive, using facial recognition to read the user’s expressions and adjust its tone accordingly. 

In a recent article published in Engineering, researchers Li Guo and Jinghai Li from the Chinese Academy of Sciences explore the future development of artificial intelligence (AI), emphasizing the need for consistency in the logical structures of datasets, AI models, model-building software, and hardware. They argue that while current AI systems excel at handling statistical properties of complex systems, they face challenges in effectively representing spatiotemporal complexity patterns. The authors propose integrating principles of multilevel complexity into AI development to enhance its functionality and reliability in engineering applications.

Perovskite-structured BaFe_0.4Co_0.4Zr_0.1Y_0.1O_3-δ (BFCZY) exhibits proton-electron-oxygen ion triple conductions and high catalytic activity of oxygen reduction (ORR) and oxygen evolution reaction (OER) at low temperatures. Although it has stability problems in a humid air environment, the degradation mechanism of BFCZY and the influences of temperature, steam content and polarization on its stability have been rarely studied. The activity and stability of the BFCZY oxygen electrode are significantly improved through heterointerface engineering by infiltrating the BaCoO₃ (BCO) catalyst. It is imperative to fill this research gap, as it is crucial for promoting the commercial development of reversible protonic ceramic electrochemical cells (R-PCECs).