Precisely how I feel. Also, what's the deal with the ports? At the moment it seems that you have to carry a dongle/adapter for every single Apple device, that's crazy. After eight years with my macbook it's time to give linux a real shot on my next laptop.
Regardless the impact machine learning techniques are having on the field, I still think is valuable to know and understand what are the classic methods that they are allegedly replacing.
Agreed. I think that's the key, you learn by first grasping a basic understanding of a concept and then reinforcing it through application repetition. But the initial understanding is absolutely vital, otherwise chances are you end-up in the mindless rote repetition you mentioned.
I've got both a Nespresso and a simple manual Gaggia at home. The Nespresso is just accumulating dust. No matter what capsules you buy it doesn't get any closer to the taste of just average coffee (that would be Lavazza Oro) on the Gaggia machine.
Not sure if it's just melancholia, but I do think rdio is still totally unbeaten in terms of personalised playlists. It was absolutely amazing! Also, the audio quality seemed far superior compared to Spotify or Apple Music.
> Although, in my experience of using vim, the mental effort of working out what character I needed for t/f tended to be far more disruptive than just using arrow keys/mouse.
I think you maybe didn't give it enough time. What really happens after a while is that you don't have to do any mental effort to do very complex things fast and efficiently. My experience is that after three months I had some sort of clicking in my head and everything made sense.
Said that, I wouldn't mind Ctrl-D on vim though, that's one of those sublime's features that I really like (and non consecutive multi line editing).
If you are referring to Morton's interleaving, then it's quite simple. You can compute the third operand's code and OR it with the others using the appropriate shift. Something like: (z << 2) | (y << 1) | x
Don't quite agree, most recent works produce 3D models of very decent quality. Have a look at this https://www.youtube.com/watch?v=XySrhZpODYs for example, but there are others based on volumetric data-structures that give fine results as well.
I'm sorry, I don't really have a source. My observation is based on the fact that during PhD/PostDoc years you have more time to spend on actual research. As you climb the academic ladder it is very probable that administrative/supervising/teaching duties become central to your job (unless you really don't want to).
Incidentally I remember also reading [1] that in certain fields, in this case mathematics, most of the groundbreaking research comes from younger mathematicians. Great contributions to the field from people over 40 are extremely rare.
[1] Simon Singh, Fermat's Last theorem. Ok, not great source but still!
I quite agree that the post PhD job market is kind of challenging as there are few companies tackling big questions.
However, if you forget the job market, the argument the guy is making is absolutely spot on. There's a solid trend in academia that is "publish early, publish fast". Although one might argue that it actually makes sense (career-wise or whatever), it is intrinsic in such a system to penalise pursuing big, risky ideas. Considering that the PhD (and the few years after) are the most productive in a researcher's life, it is a shame that students are not actively encouraged to think bigger.
Yes I do agree with you. ACL is just an example of as the devotion of one or two persons can bring unexpectedly successful results. Achieving the same in bigger organisation is a much harder challenge.
Totally agree. Just wanted to stress how the grant funding systems is totally nonsensical. While as a PhD you could get funding for your entire 3/4 year program (at least here in the UK), if you decide to go for a post-doc things get dramatically complicated as your employment is (usually) tied to a particular grant. When the grant expires, you're out if there isn't another source of money. Is that a decorous situation for a highly skilled person who devoted much of his life to studies? Not sure about that.