I am referring to direct comparisons in Cheng et al and in Stronger Baselines that everyone is discussing. Let's assume your point about "might have been insufficient". We don't currently have the luxury to be frequentists, as we don't have many academic groups reporting results for running Google code. From the Bayesian perspective, that's the evidence we have.
Maybe you know more such published papers than I do, or you know the reasons why there aren't many. Somehow this lack of follow-up over three years suggests a dead-end.
As for "belittle", how would you describe the scientific term "regurgitating" used by Jeff Dean? Also, the term "fundamentally flawed" in reference to a 2023 paper by two senior professors with serious expertise and track record in the field, that for some reason no other experts in the field criticize? Where was Jeff Dean when that paper was published and reported by the media?
Unless Cheng and Kahng agree with this characterization, Jeff Dean's timing and language are counterproductive. If he ends up being wrong on this, what's the right thing to do?
Maybe you know more such published papers than I do, or you know the reasons why there aren't many. Somehow this lack of follow-up over three years suggests a dead-end.
As for "belittle", how would you describe the scientific term "regurgitating" used by Jeff Dean? Also, the term "fundamentally flawed" in reference to a 2023 paper by two senior professors with serious expertise and track record in the field, that for some reason no other experts in the field criticize? Where was Jeff Dean when that paper was published and reported by the media?
Unless Cheng and Kahng agree with this characterization, Jeff Dean's timing and language are counterproductive. If he ends up being wrong on this, what's the right thing to do?