Hi Mark,
responsible people are resigning from X.
Cheers,
Tim
Am 01.12.2023 23:24, schrieb Mark J. van Raaij:
just came across this critique of that paper on Twitter:
This exciting paper shows AI design of materials, robotic synthesis.
10s of new compounds in 17 days. But did they? This paper has very
serious problems in materials characterisation. In my view it should
never have got near publication. Hold on tight let's take a look 😱
[1]
Robert Palgrave (@Robert_Palgrave) on X [1]
twitter.com [1]
but I'm not enough of an expert to judge - perhaps some
characterizations were wrong and a lot of the paper does stand.
On 1 Dec 2023, at 20:51, Bryan Lepore <bryanlep...@gmail.com> wrote:
Adding to that literature list a bit outside :
Merchant, A., Batzner, S., Schoenholz, S.S. _et al._
Quote:
"... we show that graph networks trained at scale can reach
unprecedented levels of generalization, improving the efficiency of
materials discovery by an order of magnitude. "
Scaling deep learning for materials discovery.
_Nature_ (2023), November
https://doi.org/10.1038/s41586-023-06735-9
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Links:
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[1] https://twitter.com/Robert_Palgrave/status/1730358675523424344
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Tim Gruene
Head of the Centre for X-ray Structure Analysis
Faculty of Chemistry
University of Vienna
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