This is the best summary I could come up with:

Two materials scientists affiliated with UC Santa Barbara have analyzed a Google paper published in Nature last November and conclude that it promises more than it delivers.

In November 2023, Google DeepMind boffins Amil Merchant and Ekin Dogus Cubuk announced the publication of a paper in the scientific journal Nature titled, “Scaling deep learning for materials discovery.”

GNoMe has expanded the number of materials available to science by discovering crystalline structures, “many of which escaped previous human chemical intuition,” the authors claim.

Among these candidates are materials that have the potential to develop future transformative technologies ranging from superconductors, powering supercomputers, and next-generation batteries to boost the efficiency of electric vehicles."

The two UC Santa Barbara boffins argue the DeepMind predictions “are solely of crystalline inorganic compounds and should be described as such, rather than using the more generic label ‘material.’”

“However, as I hope our article makes clear, we do believe that AI has a great future in the area when it is combined with first-class domain expertise from materials scientists.”

The original article contains 684 words, the summary contains 172 words. Saved 75%. I’m a bot and I’m open source!

The paper linked from the article reads more like an academic attempt at a dis-track than something written in “the spirit of conductive criticism.”

I don’t know enough about the field of study to understand what they’re saying but it’s still amusing to read for the tone alone.