Nature confirmed to reporters that they are investigating the paper. https://www.theregister.com/2023/03/27/google_ai_chip_paper_...
Note just the tone difference as you read Igor’s work to the stuff of his detractors. One immediately goes personal, tries to figure out motivations of the opposing counsel, talks about harassment and sounds emotional to say the least. The other has an extremely objective tone, only focuses on the subject matter, and in general reads more like a maths theorem than an activist essay.
I’ll leave you to guess who sounds like who.
> [2] https://twitter.com/JacobSteinhardt/status/15215993404137881...
The other two sources make concrete claim that in mid-2002 there was an independent, open-source, replication of the Nature paper:
> [1] https://twitter.com/ZoubinGhahrama1/status/15122035096467415...
>> Google stands by this work published in Nature on ML for Chip Design, which has been independently replicated, open-sourced, and used in production at Google.
> [3] https://twitter.com/sguada/status/1521587406385807361
>> The results in the Nature paper were independently replicated and validated by my team, the results were used in actual chips and Sat and his collaborators know it.
>> Furthermore, the code was open-sourced.
>> It is sad that you are providing a platform for someone's resentments.
The claims about independent replication refer to Google's circuit_training repository[1]. The UCSD team has conclusively shown this claim was materially false (see section 3 of their paper[2]).
BTW, Prof. Andrew Khang, who headed the UCSD effort, initially wrote an exteremely favorable editorial about the Nature paper[3].
[1] https://github.com/google-research/circuit_training
This was covered previously in the press and on social media, with statements from a variety of prominent researchers (e.g. https://twitter.com/JacobSteinhardt/status/15215993404137881... and https://twitter.com/sguada/status/1521587406385807361).