tag: ML

AI Meets Device Modeling: Transforming Compact Modeling With Machine Learning
By Yiao Li - 28 Aug, 2025 - Comments: 1

As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure reliable circuit simulation and design. Correspondingly, these accuracy requirements raise demands on the accuracy and efficiency of device modeling. Modern device models often involve hundreds o... » read more

AI, From A To Z
By Ed Sperling - 15 Aug, 2025 - Comments: 0

First in a seven-part series: What's the difference between AI, ML, DL, LLMs, and agentic AI? Is it truly revolutionary, or is it an evolutionary series of steps that have enabled machines to do much more than in the past? Jon Herlocker, vice president and general manager of software analytics at Cohu, talks about the evolution of AI over nearly 70 years, the chain of innovation that has enable... » read more

AI, Product Lifecycle Management, Market Dynamics: Q&A With Jay Vleeschhouwer Of Griffin Securities 
By Bob Smith - 24 Jul, 2025 - Comments: 0

In the world of EDA, Jay Vleeschhouwer, managing director of software research at Griffin Securities, needs no introduction. His presentation on the State of EDA is standing room only at the yearly Design Automation Conference (DAC). He recently agreed to a discussion with me where we talked about AI and EDA, an interesting development with product lifecycle management and global dynamics af... » read more

Cut Defects, Not Yield
By proteanTecs - 14 Jan, 2025 - Comments: 0

Many chipmakers face a difficult trade-off — improve quality without affecting yield. Traditional testing methods fail to navigate this challenge due to their limited visibility below the pass/fail limits, discarding perfectly good chips or letting small defects slip through to the field. The challenge is clear: manufacturers must achieve both quality and yield goals without sacrificing one f... » read more

Goal-Driven AI
By Brian Bailey - 26 Nov, 2024 - Comments: 2

For many, the long-term dream for AI within EDA is the ability to define a set of goals and tell the computer to go design it for them. A short while later, an optimized design will pop out. All of today's EDA tools will remain hidden, if they even exist at all. You would only be limited by your imagination. But we also know that AI is not to be trusted today, especially when millions of dol... » read more

To (B)atch Or Not To (B)atch?
By Steve Roddy - 18 Nov, 2024 - Comments: 0

When evaluating benchmark results for AI/ML processing solutions, it is very helpful to remember Shakespeare’s Hamlet, and the famous line: “To be, or not to be.” Except in this case the “B” stands for Batched. Batch size matters There are two different ways in which a machine learning inference workload can be used in a system. A particular ML graph can be used one time, preced... » read more

AI’s Power To Transform Semiconductor Design And Manufacturing
By John Kibarian - 28 Oct, 2024 - Comments: 0

Artificial intelligence and machine learning (AI/ML) have immense power to transform semiconductor design and manufacturing for a variety of broad and far-ranging applications. Just consider the volume of data generated by design and manufacturing each year. With increasingly complex products, machines, processes and supply chains, the overall amount of data associated with semiconductor making... » read more

ML Model Usage For Various Life Stages Of Semiconductor Test
By Shinji Hioki - 15 Oct, 2024 - Comments: 0

By Shinji Hioki and Ken Butler From development through high volume manufacturing (HVM), semiconductor manufacturers’ pain points change based on the life stages. Each stage requires different types of applications to help with business needs. At the early stage, where the design and process are still immature, understanding the root causes of maverick material and implementing fixes is th... » read more

Increasing Roles For Robotics In Fabs
By Gregory Haley - 19 Aug, 2024 - Comments: 0

Different types of robots with greater precision and mobility are beginning to be deployed in semiconductor manufacturing, where they are proving both reliable and cost-efficient. Static robots have been used for years inside of fabs, but they now are being supplemented by collaborative robots (cobots), autonomous mobile robots (AMRs), and autonomous humanoid robots to meet growing and widen... » read more

AI/ML’s Role In Design And Test Expands
By Laura Peters - 06 Aug, 2024 - Comments: 1

The role of AI and ML in test keeps growing, providing significant time and money savings that often exceed initial expectations. But it doesn't work in all cases, sometimes even disrupting well-tested process flows with questionable return on investment. One of the big attractions of AI is its ability to apply analytics to large data sets that are otherwise limited by human capabilities. In... » read more

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