Your buddy is totally wrong . You can be fired for talking shit , you can be fired for liking the chargers , you can be fired for wearing too much blue . It is not discriminatory to fire someone for talking shit . <| sep |> no thanks i could do it for the sienna looper ? <| sep |> I can ' t stand any CBS announcer . Especially CFB <| sep |> You must not play WoW then wait times are usually a day or 2 but usually get good responses . <| sep |> Is this inspired by the Alton Towers runaway mine train ? <| sep |> First There is a lot of incremental stuff coming out of labs that are meant to work on solving intelligence . Machine learning is still largely a ' find the lowest hanging fruit ' game . To DeepMind ' s credit , they have done a lot to change this . They have a number of huge , ambitious , and very valuable projects and it ' s great . So this distinction on focus is mostly philosophy anyway . It ' s also different that in one approach you ' re really focusing on a technique e . g . deep learning while in the other you ' re focused on a goal i . e . intelligence even if it ' s poorly defined . Notice I wrote We need to find and characterise a few situations that our human intelligence can solve but which appears to be clearly beyond reach for machine learningbased systems . So I ' m approaching this at a computational level , not at all at algorithmic or implementation level . And at the algorithmic level , I am more interested in understanding the boundaries of any machinelearningbased approach , where most of the ' intelligence ' is created by learning from experience . Even this is a lot broader focus than deep learning . Both approaches might point to asking the same question , for example Can we be superhuman performance in oneshot learning in particularly defined general scenario ? The difference is whether you came up with a question by trying to find the hardest problem because you expect the answer to be no , or your goal is to find a question to which the answer is most likely no or whether you were trying to find the easiest unsolved problem because you ultimately expect that the answer will be yes , and you are looking for questions to which the answer is most likely yes .