This paper builds off of DeepMind's previous work on differentiable computation: Neural Turing Machines. That paper generated a lot of enthusiasm when it came out in 2014, but not many researchers use NTMs today.
The feeling among researchers I've spoken to is not that NTMs aren't useful. DeepMind is simply operating on another level. Other researchers don't understand the intuitions behind the architecture well enough to make progress with it. But it seems like DeepMind, and specifically Alex Graves (first author on NTMs and now this), can.
The feeling among researchers I've spoken to is not that NTMs aren't useful. DeepMind is simply operating on another level. Other researchers don't understand the intuitions behind the architecture well enough to make progress with it. But it seems like DeepMind, and specifically Alex Graves (first author on NTMs and now this), can.