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Using ML In Manufacturing


How to prevent early life failures by applying machine learning to different use cases, and how to interpret models for different tradeoffs on reliability. Jeff David, vice president of AI solutions at PDF Solutions, digs down into how to utilize data to improve reliability. » read more

Using Machine Learning To Gain Data Insights


Today’s consumers have little appetite for networks that go down, for electronic devices that fail, and for any kind of digital service that doesn’t deliver as promised every time. Reliability is no longer a nice-to-have. It's  a key feature. The continued scaling of advanced electronics and chip manufacturing technologies, however, makes reliability harder to achieve — even as expectati... » read more

Using Machine Learning To Break Down Silos


Jeff David, vice president of AI solutions at PDF Solutions, talks with Semiconductor Engineering about where machine learning can be applied into semiconductor manufacturing, how it can be used to break down silos around different process steps, how active learning works with human input to tune algorithms, and why it’s important to be able to choose different different algorithms for differ... » read more

Adaptive Test With Test Escape Estimation for Mixed-Signal ICs


Abstract: The standard approach in industry for post-manufacturing testing of mixed-signal circuits is to measure the performances that are included in the data sheet. Despite being accurate and straightforward, this approach involves a high test time since there are numerous performances that need to be measured sequentially by switching the circuit into different test configurations. Adapt... » read more