Exploring the Value Spaces of Human Translation in the ChatGPT Era and the Transitions Needed for Translation Education

Based on metal-oxide-semiconductor field-effect transistor (MOSFET) devices and Von Neumann architecture semiconductor chip technology has led mankind into the information age. In recent years, new computing architectures have flourished. However, specialized algorithms and When mapping brain-like intelligent algorithms to MOSFET circuits, they usually face challenges such as high hardware overhead and low system energy efficiency. In response to the above problems, this paper developed a New transistor devices with the characteristics of fusion of storage and calculation are effectively adapted to special algorithms and brain-inspired computing applications: in terms of basic numerical calculations, for polynomial calculations, A charge-trapping transistor was developed, utilizing the intrinsic nonlinear dynamic characteristics of the device to realize three-element multiplication operations based on a single device, effectively accelerating multiple Nominal regression task; In terms of emerging intelligent computing, ion-gate neuromorphic transistors have been developed for neural network calculations, using dual-gate coupling. It realizes the nonlinear activation of neurons and the integration of spatiotemporal information, and based on this, a neuron correlation spiking neural network is proposed to achieve attention switching. Simulation of changing phenomena. The work of this article will provide new ideas for the construction of new computing architecture chips.