News for hackers. Stuff that matters.
Re:AI in drug discovery is overhyped: examples from AstraZen... by blueblob on Friday January 05, 2018 @02:47PM (#16081079)
Agreed. Just because you don't compare your model to another model doesn't mean you're hiding something and it's irresponsible to pretend that's the case. Perhaps the author should have run char-cnn against data instead of making baseless accusations.

On the whole, a lot of the arguments are realistic of ML in general. There is far too much focus on individual problems and the accuracy measure without enough focus on the interpretation of the accuracy, how well it will really generalize, etc.

Re:AI in drug discovery is overhyped: examples from AstraZen... by mostafab on Friday January 05, 2018 @05:52PM (#16082486)
In general, you are right. But in this particular case, char-CNN is the standard used by many people, Stanford included. It is not sophisticated at all.

Look at the big list of exotic models they tried: http://moleculenet.ai/models

For me, this omission is a negligence. It is selective laziness.

The author (me) does not have 20 PhD students, postdocs and startuppers under his hand, to do the job for Stanford. With my limited resources, it is more cost-effective to do my job against Stanford ;)

Re:AI in drug discovery is overhyped: examples from AstraZen... by dekhn on Saturday January 06, 2018 @10:18AM (#16085593)
It sounds like you have axe to grind against well-funded professors, not that you actually have a valid argument.
Re:AI in drug discovery is overhyped: examples from AstraZen... by mostafab on Saturday January 06, 2018 @08:25PM (#16088530)
This professor gave an argument in his paper. I gave a refutation. If you agree with him that char-CNN was a sophisticated model in early 2017, then you are not well-informed about the situation in deep learning.

The MoleculeNet co-author gave another argument in the comments. My refutation is that you can't claim to lack time after 8*20 man-months have passed.