I think this is overindexing on Dr. Kahng (and his accomplishments) and missing the bigger argument, which I'll restate as: if this research has merit, Google s

I think this is overindexing on Dr. Kahng (and his accomplishments) and missing the bigger argument, which I'll restate as: if this research has merit, Google should apply it to their silicon design. Then they can have a paper about how ML helped their world class engineering team create an even better chip, save design time, etc. If the research translates to strong business results, it really doesn't matter what an external researcher thinks about it. While it's possible to slap a label of ML on a mediocre product for marketing purposes, a strong and experienced engineering team generally won't use a new tool if it doesn't make their workflow substantially better.