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While I have no doubt that Google is working on machine learning applications for chip design, there have been a number of concerns raised with that paper:

https://retractionwatch.com/2023/09/26/nature-flags-doubts-o...




Nothing like a bit of good ole fashioned academic fraud to start off the day. That's fairly interesting, thanks.


We have reached a stage where open papers on this kind of research are practically impossible: either google releases all data and code, and loses potential commercialisation value, or publishes a paper which no one can reproduce and is indistinguishable from exaggerated marketing material.


Most papers out there are not reproducible because either the code or the data is not publicly available.

Somehow this is perfectly acceptable.


It’s acceptable in this context because there isn’t a good alternative. You either make the code and data available and lose all commercial value, or you publish a redacted paper and lose scientific value.

I suspect the best solution is reform of the patent system that allows a trusted third party to verify research outcomes that are registered. E.g. the code and data are available to the patent office only for verification of the results.

In terms of the rest of academia, non-open results are acceptable because those in power (institutions, journals) don’t care.




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