MIT asks arXiv to withdraw preprint of paper on AI and scientific discovery

First impressions:

1. The data in most of the plots (see the appendix) look fake. Real life data does not look that clean.

2. In May of 2022, 6 months before chatGPT put genAI in the spotlight, how does a second-year PhD student manage to convince a large materials lab firm to conduct an experiment with over 1,000 of its employees? What was the model used? It only says GANs+diffusion. Most of the technical details are just high-level general explanations of what these concepts are, nothing specific.

"Following a short pilot program, the lab began a large-scale rollout of the model in May of 2022." Anyone who has worked at a large company knows -- this just does not happen.

>The data in most of the plots (see the appendix) look fak

Could a Benford's Law analysis apply here to detect that?

How would you apply it, why would it be applicable?

Fake data is usually too clean

And? How is that at all a relevant observation?

Anyone looking at inly the data objectively should br able to comento terms that is distribution is unnatural, as it turns out to fake organic isnt as easy