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Naive question: Has anyone tried to whack these questions with the machine learning hammer? I figure if we can do protein folding [0], we should be able to do k
by spekcular 5y ago
Naive question: Has anyone tried to whack these questions with the machine learning hammer? I figure if we can do protein folding [0], we should be able to do knives.
[0] https://deepmind.com/blog/article/alphafold-a-solution-to-a-50-year-old-grand-challenge-in-biology https://deepmind.com/blog/article/alphafold-a-solution-to-a-...
- chas 5y agoFolks are certainly working on it from many dimensions, but it’s a pretty hard problem since getting ground truth data involves making and testing materials, which is a very different problem to automate than training machine learning models. You need a fairly cross disciplinary team to make progress. As an example of folks doing good work: https://a3md.utoronto.ca/ https://a3md.utoronto.ca/
- sseagull 5y agoI don’t believe we have a good way to compute various macro properties of something like steel. We can compute density and what not, but how much it holds its sharpness or something is something I haven’t seen. So I am not sure how to get the training data needed for ML. (Computational chemist, but not computational materials scientist. So could be wrong!)
- mensetmanusman 5y agoKind of, deepmind actually recently published results in metal oxides: https://ai.googleblog.com/2021/10/finding-complex-metal-oxides-for.html?m=1 https://ai.googleblog.com/2021/10/finding-complex-metal-oxid... Steel has similar complexity since the number of combinations is so vast.