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Comment by cs702 | Hacker News Reader

For background, read this fantastic blog post by the same author, Mohammed AlQuraishi at Harvard Medical School, from a year ago:

https://moalquraishi.wordpress.com/2018/12/09/alphafold-casp...

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Thanks for posting, it was a great read.

I especially enjoy the segments where he upfrontly addresses "an indictment of academic science" and "an indictment of pharma". He pulls no punches in saying how embarrassing it is for pharma and academia to be literally outclassed by DeepMind.

A great quote:

"If you think I’m being overly dramatic, consider this counterfactual scenario. Take a problem proximal to tech companies’ bottom line, e.g. image recognition or speech, and imagine that no tech company was investing research money into the problem. (IBM alone has been working on speech for decades.) Then imagine that a pharmaceutical company suddenly enters ImageNet and blows the competition out of the water, leaving the academics scratching their heads at what just happened and the tech companies almost unaware it even happened."

nobody is embarassed here. pharma doesn't work on protein folding prediction. now they can take the published results and code and use it, but protein fold prediction has not, is not, and probably will not ever be the rate limiting step in novel drug discovery and development.

Really good read! They requested the author submit it as a journal letter. This quote stuck out to me: "Keep in mind that unlike other areas of machine learning, new protein structures are not appearing at an increasing rate, and so waiting things out will not help."

Lovely read

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