[HarryHirsch]

What's worrisome is that on the graphical abstract you have nucleophilic substitution in the neopentyl position, a reaction every chemist knows won't proceed rapidly. And it takes place in dimethyl ether solvent, which every chemist knows it's a gas.

It looks a bit what you see in bad teaching materials, chemistry that is almost correct, but won't work well for some reason we are not telling the kids about. Please alleviate my concerns! :-)

[jnwei]

This is Jennifer, another of the authors. You're absolutely right about the graphical abstract figure. For this first paper, we used very simple rules to generate our data set of reaction, so you end up with reactions that don't fully capture a human chemist's intuition.

We hope in the future to have access to real experimental data sets for real chemistry, complete with accurate temperatures, pressures, solvents, and reaction yields. Then our algorithm would be able to use all the information and predict reactions accurately. Right now, there just aren't many well-curated data sets with this kind of detail that would work for this kind of training. Happy to receive feedback from any experimental chemists out there with data from their research that they'd like to train on.

[duvenaud]

That diagram is just meant to show what type the inputs and outputs of the neural network are. I'm not a chemist myself, but the other two authors are.

[chillacy]

Heh, not a chemist either, but the parent probably has the same feeling I get when I watch "hackers" in crime dramas break into systems and see a bunch of HTML and CSS on their terminals.