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Abstract With a large number of film capacitors being deployed in critical locations in electrical and electronic systems, artificial intelligence (AI) technology is also expected to address the problems encountered in this process. According to our findings, AI applications can cover the entire lifecycle of film capacitors. However, the AI safety hazards in these applications have not received the attention they deserve. To meet this, the authors argue, with specific examples, risks that flawed, erratic, and unethical AI can introduce in the design, operation, and evaluation of film capacitors. Human‐AI common impact and more multi‐dimensional evaluation for AI are proposed to better cope with unknown, ambiguity, and known risks brought from AI in film capacitors now and in the future.

In this paper, a wideband differential phase shifter has been analyzed and designed using Genetic Algorithm (GA). The differential phase shifter consists of two fixed main lines of length λ/2, and parallel open and short stubs of length λ/8, which are shunted at the edge points of the main lines, respectively. With the application of GA, an impedance match and minimum phase deviation for the desired phase shift over a wide frequency band are obtained. In order to verify the optimum results, simulation experiments are made and a 45° phase shifter is fabricated and measured. The phase shifter exhibits an impedance bandwidth (|S11| < -10dB) and a consistent 45° (±2°) phase difference bandwidth around 66%. [ABSTRACT FROM AUTHOR]