2,177 karma · joined February 25, 2014
[ my public key: https://keybase.io/khllkcm; my proof: https://keybase.io/khllkcm/sigs/E94-JbalPg0U9paAIK4rL8loPzAKv1dyikzSRiUkjNQ ]
0.http://www.google.com/design/spec/resources/sticker-sheets.h...
I don't know about German but French? easier than English? Come on!
https://www.youtube.com/watch?v=HEe3xfWfkG8
I am curious to know how such footage is shot.
Oh yeah! I don't know about now though, it sure used to be. I didn't do anything fancy, just some basic bot automation and a couple miscellaneous chatbox-based addons (mostly for spamming) but it got me learning Lua.
Edit: Looks like LoL is still moddable via Lua[0]
Being the 21-year-old guy who didn't learn how to ride a bike when growing up I am, this has actually motivated me to do exactly that, as a start.
The whole assertion of "understanding how a proof is done rather than memorizing it is how maths should be done" holds true, BUT only when you are not bound by time or a deadline, which is not the case most of time, whether you are working through a test, an exam or even on a PhD, you cannot afford losing time "reinventing the wheel"; working on proving theorems that have already been proven rather than using them directly.
The factor of time forces you to "memorize" certain concepts/theorems/facts so that you can use them directly as tools.
Personally, my approach consists in working on proving these "tools" at a first stage; understanding why they are true, then, I simply go past that and simply "memorize" them in order to boost my workflow.
In a nutshell, in order to be productive (doing maths or even physics), you must memorize shit, just don't do it blindly.
This book is dense. But takes three times as long to read as any fiction that length. Most paragraphs require stopping and pondering.
It is my second time attempting to read this book. The first time, was about 6 months ago. Now, being on my second year in CPGE and having been through quite some math, it was more approachable.
Hofstadter invents his own system of formal mathematical logic and his own procedural programming language to explain concepts, without going into what would be considered a more "standard" formal logic system or even the Turing machine itself. He does a good job piecing them together but at certain times I feel like it'd be more meaningful to read the original works on several of the subjects he touches on.
While formal logic certainly predates this book, a lot of the AI and neuroscience research that he describes were (and are) very much active. The book was published in 1979, and its references to AI reflect the time period.
The book is hard to read, especially for prolonged periods of time. It's dense and the concepts are not the easiest to begin with.
Worth reading? Maybe.
Will it expand your thinking? Probably, though maybe not as much as you might expect; due to the broad spectrum of topics covered, it's not as deep as I would like in some areas and spends too much time smoothing over difficult topics in certain fields in order to make "clever" maps between concepts in the fields (though in this aspect he's just being a computer scientist---simple representations that map cleanly across everything! Sadly, the world is not that way).
Very good? Absolutely.
What technologies did you use?
0.http://en.wikipedia.org/wiki/Old_Turkic_alphabet#Table_of_ch...
Edit: Some characters don't seem to render properly, an Image seems more practical. http://en.wikipedia.org/wiki/Old_Turkic_alphabet#mediaviewer...
If your account is less than a year old, please don't submit comments saying that HN is turning into Reddit. (It's a common semi-noob illusion.)
First world problem.