Hello World

To blog or not to blog, that is the question. And, increasingly, the former has seemed like the better option. Every so often, I get the itch to write, and it seems a waste to ignore it. I try to have interesting conversations with interesting people, and it seems a waste if they're not recorded. I also have fairly disparate interests, and I'm hoping a blog will funnel me into exploring them on a more systematic basis.

To start off with, I've put up a number of projects of mine in the Programming and Learning & Teaching tabs. I'll be making posts with some commentary on these later. They cover quite an eclectic range of subjects. Some were motivated by my own curiosity, essentially me taking notes as I learned about a topic. Some were intended as presents for my siblings, to help them explore areas they were interested in (living overseas, I've started coming around to my dad's view that "the best presents are virtual ones"). The programming projects (more to come up later) were largely inspired by some interesting Oxford courses that I took. If you've got any thoughts/comments/corrections on any of them, do drop me a line.

Lastly, I should probably explain the title of this blog. It definitely doesn't mean that all the thinking has been done already. A better interpretation is that it's describing broad and holistic thinking, which this blog definitely aims to do. But in fact, it's mostly a computer science reference. A "complete" problem is one which is at least as hard as every other problem in its class. For example, a problem is P-complete if any other problem which can be solved in a polynomial number of steps can be reduced to that problem. One of the most well-studied complexity classes is NP-complete problems, which are key to the most important unsolved problem in computer science. So if something is thinking complete, then it is one of the hardest problems in the class of all problems which can be solved by thinking.

Taken literally, there might be two problems in that group: creating general AI, and convincing a lot of very competent people to work for or with you (both interests of mine, in fact). All other problems reduce to these, since if you can do either of them, you can use that to solve any other thinking-related problem. But in a broader sense, it's about a certain mindset. Richard Hamming (inventor of the first perfectly efficient code) used to go around asking his colleagues: "What's the most important problem in your field, and why aren't you working on it?" Perhaps it's not realistic to work on all the best problems out there, but it's certainly realistic to blog about them. So, time to get started.


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