Deepmind being a machine learning/statistics/maths/computer science fuelled company, it made sense for the interview process to follow this simple organisation.
I was however very disappointed by the questions asked for each part. Not a single one of the ~100 questions asked during these 3h of my life demanded some "problem solving" skills, only encyclopaedic knowledge (describe this algorithm, what is a Jaccobian matrix, define what an artificial neural network is, what is polymorphism, give examples of classifiers, what are the conditions to apply a t-test...)
So what if someone doesn't remember every definition of the stats/ML/CS/Maths respective bibles as long as they're clever enough to look it up and understand quickly what's needed?
I mean, I get it these are very basic questions but as a highly qualified interviewee who necessarily has other offers given this set of skills, this fastidious, back to school, time wasting process does not reflect well on the company and makes me consider my other options even more seriously.
Knowing what a classifier is is simply more than encyclopedic knowledge that you should probably know before joining an AI company.
Making them face a simple stats/CS/maths/ML problem and see if he/she is able to come up with the relevant concepts is far more interesting.
But if you don't think they did that at all then I guess that's bad!
I generally am for the "look things up" argument, but so many people in tech take that to an extreme of "I can fully understand an entire discipline by looking at the Wikipedia page for 5 minutes".