Earlier quoted context omitted.
After six or seven click-throughs, I downloaded the PDF. I haven't read it but skimming, I could see that there definitely were no formulas in it at all . Which sort of says, at best what it tells you is "we did this thing, which is kind of like X and kind of like Y with Z changes". Essentially, no way to reproduce or understand by itself. The first reference then had a link behind a paywall... So despite lots of app…
70 page supplementary material: http://science.sciencemag.org/content/sci/suppl/2017/10/25/s... Reference code: https://github.com/vicariousinc/science_rcn
I still find it incredibly hard to tell whether this is overblown hype or legit scientific progress. There is no indication whatsoever that this approach scales to deep feature hierarchies and that is likely what you need to compete on hard tasks like classification on ImageNet. Given the amount of money at play (several hundred millions of dollars), writing 70 pages, making code publishable is certainly an obvious way to get the most out of the hype.