In today’s semiconductor industry, machine learning (ML) is no longer a buzzword — it’s an operational necessity. From optimizing test flows to identifying device drifts and executing advanced analytics like VMIN or trimming, ML-based applications are increasingly used to boost yields, improve quality, and lower test costs. But there’s a catch.
To make these intelligent applications ...
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