I don't think enough people appreciate (or understand) your point 4. I am fairly good at algorithmic optimizations and pretty good at your implementation optimizations, but I do not have the math to do much mathematical optimizations, so spending any time on these kinds of problems gives me a visceral understanding of your point 8.
But I've talked to too many people who don't understand that such problems exist, and therefore don't see the point of any optimization (and then wonder why others consider their products to be hideous monstrosities), or believe that micro-optimizations or algorithms are the best you can do. In reality, all three are closely tied together and, in fact, applicable to almost any problem.
Your points 6 and 7 could be elaborated more. Or at least stamped on the foreheads of some educators of my acquaintance. One of the things I learned from what math education I have had is that you won't really understand something without seriously using it.
I hope that this was actually part of your PhD research, or if not that it didn't delay you too much. And if you're out in the "real world", all you have to do to succeed is to forget you ever heard of your point 10.
It wasn't actually part of my PhD. But it didn't delay me too much in the sense that I was able to stop on time to finish my PhD work. In fact, over the next 4 month period I wrote up my thesis and coded up the prototype as well, which I hadn't done in the 3 years prior. I do conjecture that my performance in the PhD work relates to the time spent on the 17x17 but besides certain specific items, it's just conjecture.
I'm in the real world now for good, and I might be lucky that things in the class that would invoke the reaction this problem did, are few and far between. I'd like to find something that I can enjoy this much while being profitable, but, oh well, a man can dream, right?
I don't think enough people appreciate (or understand) your point 4. I am fairly good at algorithmic optimizations and pretty good at your implementation optimizations, but I do not have the math to do much mathematical optimizations, so spending any time on these kinds of problems gives me a visceral understanding of your point 8.
But I've talked to too many people who don't understand that such problems exist, and therefore don't see the point of any optimization (and then wonder why others consider their products to be hideous monstrosities), or believe that micro-optimizations or algorithms are the best you can do. In reality, all three are closely tied together and, in fact, applicable to almost any problem.
Your points 6 and 7 could be elaborated more. Or at least stamped on the foreheads of some educators of my acquaintance. One of the things I learned from what math education I have had is that you won't really understand something without seriously using it.
I hope that this was actually part of your PhD research, or if not that it didn't delay you too much. And if you're out in the "real world", all you have to do to succeed is to forget you ever heard of your point 10.