[Question] ML is now automating parts of chip R&D. How big a deal is this?

Article; paper

...the authors’ floorplan solutions have been incorporated into the chip designs for Google’s next-generation artificial-intelligence processors. This means that the solutions are good enough for millions of copies to be printed on expensive, cutting-edge silicon wafers. We can therefore expect the semiconductor industry to redouble its interest in replicating the authors’ work, and to pursue a host of similar applications throughout the chip-design process.

My current guess is that this is not a big deal. Surely these AI-optimizations will result in something like 10% improvement in AI-training-FLOPS-per-dollar, not 100%+, so they won’t really change timelines or anything else strategically important. And it won’t even be 10% improvement every year from now on, but more like 10% this year, a further 5% next year, a further 2.5% the year after that, etc. as the low-hanging fruit from floorplan optimization is picked. OTOH, this plausibly will reduce the time it takes to design new chips by a lot… but I’d be surprised if that was the main bottleneck anyway. I would have thought ramping up production was the main bottleneck.

I know very little about the chip industry though. Anyone care to correct me?