Core Viewpoint - The article discusses the challenges in semiconductor parameter extraction due to the complexity of device models and the limitations of traditional optimization algorithms, introducing Keysight's ML Optimizer as a revolutionary solution to enhance efficiency and accuracy in this process [1][4]. Group 1: Challenges in Semiconductor Parameter Extraction - The complexity of semiconductor device models has made parameter extraction increasingly challenging, with traditional optimization algorithms often getting stuck in local optima due to unclear gradient changes [1]. - The presence of numerous interrelated parameters in modern semiconductor models leads to inefficiencies in traditional methods, requiring engineers to break down the extraction process into lengthy sub-steps, which can take days or even weeks [1]. Group 2: Introduction of ML Optimizer - Keysight has launched the ML Optimizer, a machine learning-based global optimizer that simplifies the parameter extraction process by synchronously handling vast amounts of data in a single step, reducing the extraction time from days to just hours [2][4]. - The ML Optimizer excels in navigating non-convex parameter spaces, utilizing advanced machine learning algorithms to find global optima more accurately, thereby improving the precision of parameter extraction and the consistency of overall fitting [4]. Group 3: Live Demonstration and Applications - A live demonstration is scheduled to showcase the ML Optimizer's effectiveness in various device modeling tasks, including diodes, GaN HEMTs, MOSFETs, and BJTs, with interactive elements and prizes for participants [4][6]. - The event will feature experts from Keysight, including application engineers and product managers, who will discuss the application of artificial neural networks and the ML Optimizer in device modeling [8][11].

Core Viewpoint - The article highlights the challenges in semiconductor parameter extraction due to the complexity of device models and the inefficiencies of traditional optimization algorithms. It introduces Keysight's ML Optimizer, a machine learning-based global optimizer that significantly improves the parameter extraction process, reducing the time from days to hours and enhancing accuracy and consistency in model fitting [1]. Group 1: Challenges in Semiconductor Parameter Extraction - The complexity of semiconductor device models has made parameter extraction increasingly challenging [1]. - Traditional optimization algorithms struggle with unclear gradient changes, often getting trapped in local optima, leading to unsatisfactory extraction results [1]. - The presence of numerous interrelated parameters in modern semiconductor models further complicates the efficiency of traditional methods, requiring engineers to break down the extraction process into lengthy sub-steps [1]. Group 2: Introduction of ML Optimizer - Keysight has launched the ML Optimizer, which utilizes machine learning to revolutionize semiconductor parameter extraction [1]. - The ML Optimizer can process vast amounts of data in a single step, greatly simplifying the parameter extraction workflow [1]. - The time required for parameter extraction is reduced from several days to just a few hours, significantly enhancing work efficiency [1]. Group 3: Advantages of ML Optimizer - The ML Optimizer excels in navigating non-convex parameter spaces, overcoming the limitations of traditional methods [1]. - It provides more accurate global optimum solutions, improving the precision of parameter extraction and the overall consistency of model fitting [1]. - This advancement offers a solid foundation for the accurate construction of semiconductor device models [1]. Group 4: Upcoming Live Event - A live event will showcase the effectiveness of the ML Optimizer in various device modeling tasks, including diodes, GaN HEMT, MOSFET, and BJT [2]. - The event is scheduled for June 10, 2025, from 14:00 to 14:45 [4]. - Participants will have the opportunity to engage in interactive activities, including a lottery for prizes [2]. Group 5: Key Speakers - Li Yiao, a device modeling application engineer at Keysight, specializes in applying artificial neural networks and ML Optimizer in device modeling [7]. - Deng Jiayuan, a product manager at Keysight, has extensive experience in providing technical support for semiconductor customers and is involved in the development of modeling products [10].