One is basically an evidence-free ad hominem attack. > [2] https://twitter.com/JacobSteinhardt/status/1521599340413788161 https://twitter.com/JacobSteinhardt/s

One is basically an evidence-free ad hominem attack. > [2] https://twitter.com/JacobSteinhardt/status/1521599340413788161 https://twitter.com/JacobSteinhardt/status/15215993404137881... The other two sources make a concrete claim that in mid-2002 there was an independent, open-source, replication of the Nature paper: > [1] https://twitter.com/ZoubinGhahrama1/status/1512203509646741507 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 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 https://github.com/google-research/circuit_training [2] https://arxiv.org/pdf/2302.11014.pdf https://arxiv.org/pdf/2302.11014.pdf [3] https://www.nature.com/articles/d41586-021-01515-9 https://www.nature.com/articles/d41586-021-01515-9