[peaceb]

First of all, interesting and fascinating work! It is nice to see some chemistry over here.

I'm a grad student in computational chemistry. I am fascinated by the idea that our imagination, or limits of our chemical intuition, is the limiting factor for all kinds of cool advances. Through that I have recently been studying machine learning and I am interested in using it for catalyst optimization and design.

What is your opinion on the state of computationally assisted inverse design of molecules and the role of machine learning in it? The problem is a bit more open-ended compared to reaction optimization, but I could imagine that after proper formulation of the design guidelines the computer could help a lot.

[duvenaud]

Thank you! I guess all you need to do to get chemistry on hacker news is add neural nets to it.

I honestly don't know much about synthesis or the state of computationally assisted inverse design of molecules, except that it seems like a great idea, and that it is still early days. As you say, proper formulation of the guidelines is still necessary - as far as I understand, right now the synthesis people still use a lot of judgement at each step, and all these little choices will have to be recorded to build a useful dataset.