5 ms·

Hey! I’m a coauthor with this guy :^). Incredibly fascinating (and extremely smart) dude. His interest in origami is what drew me to MIT in the first place, sin

Hey! I’m a coauthor with this guy :^). Incredibly fascinating (and extremely smart) dude. His interest in origami is what drew me to MIT in the first place, since I was interested in it as well from a young age. A few years ago I took his class on the computability/complexity theory of folding, and we ended up solving an open problem in the field and published a paper out of it [0]. If you had told highschool me something like that would happen, I never would have believed it :) [0]: https://arxiv.org/abs/1901.08564 https://arxiv.org/abs/1901.08564

420codebro 7y ago
That's amazing. Congrats!
mygo 7y ago
> If you had told highschool me something like that would happen, I never would have believed it :) I find it interesting that a common story of people who did big things is that nobody would have predicted they'd end up doing the things they did. Reminds me of my own reflections on things that I have done that I never would have expected I'd be doing. As well as this recent article by the creator of Entrepreneur magazine [0]. "literally nobody, myself included, would have once predicted that I’d be running a magazine called Entrepreneur" [0]: https://www.entrepreneur.com/article/331221 https://www.entrepreneur.com/article/331221
- ddxxdd 7y ago
  Someone needs to apply Bayes theorem to determine if not believing in oneself is truly a prerequisite to achieving greatness.
  - zdragnar 7y ago
    Is it "not believing in oneself" or is it "life takes unexpected turns and you don't always end up where you thought you would"?
  - tuesdayrain 7y ago
    I don't think people would even try something in the first place if deep down they didn't believe it could work out.
  - mygo 7y ago
    I don't think it's about not believing in oneself. I actually think the opposite is a requisite -- that you must believe in yourself, even if you don't know where you're heading. Or even if you know where you're heading, and it's not the path that you had originally charted. You can't see 20 moves ahead, but you know a good next move.
joe_the_user 7y ago
Hmm, Scanning the topics here, what seems really interesting is how basic data structure are, naturally, containers for data but these advanced data structures are more like "mix-ins" or effects, qualities that can be added to a container. Time travel most obviously but also the various optimizing tree containers. Not sure how to make this an interesting question. But it's interesting. How many effects can we add to a given structure? Can we make these additions automatically? Can we combine all of these or are some incompatible with each other? What are the cost-benefits between these?
amrx431 7y ago
Hi there. What would you suggest to a person who loves these kind of stuff (data structures and algorithms) but finds it hard to develop the underlying intuitions for coming up with these data-structure and algorithm? I personally just hammer down on deliberate practice to recognise patterns and underlying concepts to solve as many problems as I can on my own. I was wondering apart from general DS and Algo what topics in Mathematics might supplement this process?
- Taniwha 7y ago
  Really, to quote the old "How do I get to Carnegie Hall?" it's "practice practice practice" - it's doing this stuff often enough so that the correct data structure becomes obvious is how you get good at this game
- pfdietz 7y ago
  I recently had someone ask me about a problem in machine learning. The algorithm for it turned out to be something I had read about 30 years earlier, where it was being used to accelerate the simulation of the motion of stars in galaxies. I had never expected to use that algorithm, but its existence, if not details, was there in my long term memory, waiting to surface. So, I suggest you just read everything you can, getting the gist of things so if you encounter something similar you know where to look. I also suggest looking for little tricks you can apply again and again. For example, some of the data structures in that course use a trick where you break the structure into a top part, using one algorithm, and a bunch of leaf parts, each of size maybe O(log n), that are handled using another algorithm. Often this combination does better than either algorithm by itself.
  - amrx431 7y ago
    Few questions: 1. Where can I find that algorithm you are talking about? 2. The algorithm which you stated seems a bit complex from the algos taught in the undergrad level, so what are the pre-requisites for understanding it that I must be aware of? 3. What books or papers you would suggest for reading? 4. How the hell you remember something you read decades ago :)?
0x445442 7y ago
The first 17 minutes of the Time Travel lecture is the best introduction to Git I've seen and he didn't even mention Git.
Mijka 7y ago
Recognized his face and name instantly ! I know him by reputation from his origami work and appearance in a documentary, seems to be a very cool guy.

420codebro 7y ago

That's amazing. Congrats!

mygo 7y ago

> If you had told highschool me something like that would happen, I never would have believed it :) I find it interesting that a common story of people who did big things is that nobody would have predicted they'd end up doing the things they did. Reminds me of my own reflections on things that I have done that I never would have expected I'd be doing. As well as this recent article by the creator of Entrepreneur magazine [0]. "literally nobody, myself included, would have once predicted that I’d be running a magazine called Entrepreneur" [0]: https://www.entrepreneur.com/article/331221 https://www.entrepreneur.com/article/331221

ddxxdd 7y ago
Someone needs to apply Bayes theorem to determine if not believing in oneself is truly a prerequisite to achieving greatness.
- zdragnar 7y ago
  Is it "not believing in oneself" or is it "life takes unexpected turns and you don't always end up where you thought you would"?
- tuesdayrain 7y ago
  I don't think people would even try something in the first place if deep down they didn't believe it could work out.
- mygo 7y ago
  I don't think it's about not believing in oneself. I actually think the opposite is a requisite -- that you must believe in yourself, even if you don't know where you're heading. Or even if you know where you're heading, and it's not the path that you had originally charted. You can't see 20 moves ahead, but you know a good next move.

joe_the_user 7y ago

Hmm, Scanning the topics here, what seems really interesting is how basic data structure are, naturally, containers for data but these advanced data structures are more like "mix-ins" or effects, qualities that can be added to a container. Time travel most obviously but also the various optimizing tree containers. Not sure how to make this an interesting question. But it's interesting. How many effects can we add to a given structure? Can we make these additions automatically? Can we combine all of these or are some incompatible with each other? What are the cost-benefits between these?

amrx431 7y ago

Hi there. What would you suggest to a person who loves these kind of stuff (data structures and algorithms) but finds it hard to develop the underlying intuitions for coming up with these data-structure and algorithm? I personally just hammer down on deliberate practice to recognise patterns and underlying concepts to solve as many problems as I can on my own. I was wondering apart from general DS and Algo what topics in Mathematics might supplement this process?

Taniwha 7y ago
Really, to quote the old "How do I get to Carnegie Hall?" it's "practice practice practice" - it's doing this stuff often enough so that the correct data structure becomes obvious is how you get good at this game
pfdietz 7y ago
I recently had someone ask me about a problem in machine learning. The algorithm for it turned out to be something I had read about 30 years earlier, where it was being used to accelerate the simulation of the motion of stars in galaxies. I had never expected to use that algorithm, but its existence, if not details, was there in my long term memory, waiting to surface. So, I suggest you just read everything you can, getting the gist of things so if you encounter something similar you know where to look. I also suggest looking for little tricks you can apply again and again. For example, some of the data structures in that course use a trick where you break the structure into a top part, using one algorithm, and a bunch of leaf parts, each of size maybe O(log n), that are handled using another algorithm. Often this combination does better than either algorithm by itself.
- amrx431 7y ago
  Few questions: 1. Where can I find that algorithm you are talking about? 2. The algorithm which you stated seems a bit complex from the algos taught in the undergrad level, so what are the pre-requisites for understanding it that I must be aware of? 3. What books or papers you would suggest for reading? 4. How the hell you remember something you read decades ago :)?

0x445442 7y ago

The first 17 minutes of the Time Travel lecture is the best introduction to Git I've seen and he didn't even mention Git.

Mijka 7y ago

Recognized his face and name instantly ! I know him by reputation from his origami work and appearance in a documentary, seems to be a very cool guy.