Functional verification produces an enormous amount of data that could be used to train a machine learning system, but it's not always clear which data is useful or whether it can help.
The challenge with ML is understanding when and where to use it, and how to integrate it with other tools and approaches. With a big enough hammer, it is tempting to call everything a nail, and just throwing ...
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