In no particular order of categories:
Forums
Shopping
Books
Social
News
Calendar
Blogging
Images
Videos
Art
Programming
Music
Other
My Digital Life
Unknown, 2010-01-05
I took some time over the weekend to collect the pieces of my digital life. I present the results below, a digital scrapbook, if you will. I tried to list all services that I use. For the sites which are not social in nature, and therefore don't have a "profile" to present, I simply linked to the site homepage. Anything that is updated (and viewable publicly) at least once a year is in bold.
In no particular order of categories:
In no particular order of categories:
An Evening with Frank Warren
Unknown, 2009-12-08
Frank Warren, the guy behind PostSecret, visited Ann Arbor on Friday. He travels and gives talks on PostSecret, and having followed that blog for over two years now, I thought I would go and listen to him speak.
This is the first time I've been to any sort of ticketed event. I've never been to concerts (except free ones), or improv theaters (at least not by myself).
If people are not familiar with PostSecret, it's an online social art project. People from all over the world send postcards to Frank. Sometimes the postcards are hand made, other times they're bought, but they share one feature: the sender has written a secret on the postcard. Frank then chooses 20 or so each week (he gets hundreds) to put on the blog, as well as some email responses people have had.
For his talks, he spends some time talking about the origins of the project, then sharing some secrets which were never posted or published in his books, and talks more about the appeal of human connection. At the end, people from the audience are encouraged to share their secrets on the spot.
Personally, I thought the two hours spent was well spent, although the event overall could be better. Although I applaud Frank from coming up with the idea, when people read PostSecret it's really for what people have poured their heart out on. The catharsis is from reading the secrets, and knowing that other people have the same thoughts, feelings, and fears that you do. Knowing that, I wish Frank would have allotted more time for the audience to contribute, to build the conversation in the moment, as opposed to talking about how PostSecret came to be. He's not a bad speaker - he has done this hundreds of times before, and gets the audience to laugh when he wants them to - but it's also missing the heart of why his project is so successful.
Nothing that Frank said had much affect on me. I was more affected by a secret that someone in the audience shared, which made me feel warm and euphoric, as though I had been drinking. It was a girl, who told the story of answering the phone one day and talking to the stranger on the other end for hours. At the end, as they were about to hang up, the stranger told her, "thankyou for talking to me. I was going to kill myself before I dialed a random number..." While telling the story, the girl's voice cracked and started sobbing, no doubt reliving the powerful effect that experience had on her. As Frank pointed out, people are just looking for someone to listen, to show that they care.
Since I haven't had a complete post on PostSecret before, I thought I would also share some of the secrets which resonated with me from the blog. My old dorm did do a similar event, and you can read some of what my (really) immediate neighbors wrote. These are from the official site:
This is the first time I've been to any sort of ticketed event. I've never been to concerts (except free ones), or improv theaters (at least not by myself).
If people are not familiar with PostSecret, it's an online social art project. People from all over the world send postcards to Frank. Sometimes the postcards are hand made, other times they're bought, but they share one feature: the sender has written a secret on the postcard. Frank then chooses 20 or so each week (he gets hundreds) to put on the blog, as well as some email responses people have had.
For his talks, he spends some time talking about the origins of the project, then sharing some secrets which were never posted or published in his books, and talks more about the appeal of human connection. At the end, people from the audience are encouraged to share their secrets on the spot.
Personally, I thought the two hours spent was well spent, although the event overall could be better. Although I applaud Frank from coming up with the idea, when people read PostSecret it's really for what people have poured their heart out on. The catharsis is from reading the secrets, and knowing that other people have the same thoughts, feelings, and fears that you do. Knowing that, I wish Frank would have allotted more time for the audience to contribute, to build the conversation in the moment, as opposed to talking about how PostSecret came to be. He's not a bad speaker - he has done this hundreds of times before, and gets the audience to laugh when he wants them to - but it's also missing the heart of why his project is so successful.
Nothing that Frank said had much affect on me. I was more affected by a secret that someone in the audience shared, which made me feel warm and euphoric, as though I had been drinking. It was a girl, who told the story of answering the phone one day and talking to the stranger on the other end for hours. At the end, as they were about to hang up, the stranger told her, "thankyou for talking to me. I was going to kill myself before I dialed a random number..." While telling the story, the girl's voice cracked and started sobbing, no doubt reliving the powerful effect that experience had on her. As Frank pointed out, people are just looking for someone to listen, to show that they care.
Since I haven't had a complete post on PostSecret before, I thought I would also share some of the secrets which resonated with me from the blog. My old dorm did do a similar event, and you can read some of what my (really) immediate neighbors wrote. These are from the official site:
- "I want to tell you that i love you, but I'm afraid of the silence that might follow."
- "I am afraid that the person I would love and myself will never meet, since we would both be too introverted to introduce ourselves."
- "Today I realized I could no longer remember what you were like when you still loved me."
- "I am a virgin. I've had three girls offer me free, easy, no-commitment sex. But I turned them all down, because I'm in love with a beautiful girl who just wants to be friends."
- "I lost my virginity last night to a boy who doesn't love me... And all I care about is how I'm going to have to lie to people when they ask me if I'm still a virgin."
- "You thought you lost your /virginity/ that night. I never had the heart to tell you... /It was only my hand/."
- "I love my wife, but I don't respect her, because she's not very smart."
- "Whenever a stranger stands by me, or passes, I wonder what's on their mind and when they walk away, I secretly miss them."
- "Everywhere I look people have found someone to share their lives with. I don't think anyone is looking for me."
- "Every Valentine's Day, I go to Papyrus to rip off their card ideas."
- "I didn't take your virginity because I felt it was going to end and I love you so much I wanted it to be special for you."
- "If I could go back in time, I'd go back to all the times we almost kissed... and I'd kiss you."
- "I have pretended to be happy for so long. I don't know if I'm still pretending."
- "I love you and I know you are going to hurt me. I resent that you will hurt me, but I don't know what to do."
- "The best decision I ever made was letting you love me."
- "We accept the love we think we deserve."
Challenges
Unknown, 2009-11-20
This has been a hard week for me.
On Tuesday I got back my midterm for intro to AI. The material for the course is mostly stuff I'd already done before, so Ive never been too worried about my grade. And, seeing that I got 85% on the midterm, I was correct. What had an undercurrent of an effect on me, which I didn't feel until that evening, was that my score was below both the mean and the average.
And all of a sudden, I started questioning myself. Am I really cut out to be in grad school? Can I make the original contributions that are required of me?
Then there's the anxiety of not knowing how I did in my machine learning midterm last week. Although I have taken a machine learning course before, this course is much more statistically oriented. While I am not completely clueless about statistics, the only course I took on it was in my junior year. I was definitely not up to scratch with my probabilities and density/mass functions, and it was a struggle to understand what the class was about.
It's strange, because I imagine that's how some people must feel even in high school. For people who are not particularly gifted at math, or science, or whatever subject, being required to take those courses must have been difficult for them. I have never had that problem - most of the courses I took even in college came easily to me, and very rarely did I really have to push myself to even get by in a class. With the combination of machine learning, and being below average in AI, I got a glimpse of what school must have felt like for some people.
Last summer when I first worked at CTY, one of the things which struck me the most during orientation was something not about me or the staff, but about the kids. Someone who has worked at CTY for many years commented that while the kids can do a lot of things by themselves, at some point when they get older they /have/ to work with each other, because what they're doing is simply beyond the capability of any single person. I remembered that comment, and even put it in my journal, because I wondered if that was the case for me too. Just as before CTY the students might not have needed to work together, and therefore have poor teamwork skills, I could phrase my own life in those terms. Everything up to and including college had a fixed upper boundary on what you could do. In elementary school you had to master multiplication, in high school it was calculus, and in college some selected topics within a certain field. I was smart, so I did all this without problems, but I wasn't smart enough to skip all the way to college or grad school before my age.
But once college ends, the world is wide open. In grad school and in research, the things you are learning may not have an agreed upon answer. The question might not even have been asked. Each professor that you deal with personally have expertise, and what they studied might not even have occurred to you. It is exciting for the same reason, but it also meant that things will not come easily anymore. The material is more recent - no longer are we studying the creation of some guy in the renaissance (calculus), but concepts and algorithms developed in the last 50 years, maybe even the last 10 years.
I was just suddenly overwhelmed by all of this, and wondered if I really would make my mark among all these giants.
The feeling passed by Wednesday afternoon, but the advice remains: pull yourself together, Justin.
On Tuesday I got back my midterm for intro to AI. The material for the course is mostly stuff I'd already done before, so Ive never been too worried about my grade. And, seeing that I got 85% on the midterm, I was correct. What had an undercurrent of an effect on me, which I didn't feel until that evening, was that my score was below both the mean and the average.
And all of a sudden, I started questioning myself. Am I really cut out to be in grad school? Can I make the original contributions that are required of me?
Then there's the anxiety of not knowing how I did in my machine learning midterm last week. Although I have taken a machine learning course before, this course is much more statistically oriented. While I am not completely clueless about statistics, the only course I took on it was in my junior year. I was definitely not up to scratch with my probabilities and density/mass functions, and it was a struggle to understand what the class was about.
It's strange, because I imagine that's how some people must feel even in high school. For people who are not particularly gifted at math, or science, or whatever subject, being required to take those courses must have been difficult for them. I have never had that problem - most of the courses I took even in college came easily to me, and very rarely did I really have to push myself to even get by in a class. With the combination of machine learning, and being below average in AI, I got a glimpse of what school must have felt like for some people.
Last summer when I first worked at CTY, one of the things which struck me the most during orientation was something not about me or the staff, but about the kids. Someone who has worked at CTY for many years commented that while the kids can do a lot of things by themselves, at some point when they get older they /have/ to work with each other, because what they're doing is simply beyond the capability of any single person. I remembered that comment, and even put it in my journal, because I wondered if that was the case for me too. Just as before CTY the students might not have needed to work together, and therefore have poor teamwork skills, I could phrase my own life in those terms. Everything up to and including college had a fixed upper boundary on what you could do. In elementary school you had to master multiplication, in high school it was calculus, and in college some selected topics within a certain field. I was smart, so I did all this without problems, but I wasn't smart enough to skip all the way to college or grad school before my age.
But once college ends, the world is wide open. In grad school and in research, the things you are learning may not have an agreed upon answer. The question might not even have been asked. Each professor that you deal with personally have expertise, and what they studied might not even have occurred to you. It is exciting for the same reason, but it also meant that things will not come easily anymore. The material is more recent - no longer are we studying the creation of some guy in the renaissance (calculus), but concepts and algorithms developed in the last 50 years, maybe even the last 10 years.
I was just suddenly overwhelmed by all of this, and wondered if I really would make my mark among all these giants.
The feeling passed by Wednesday afternoon, but the advice remains: pull yourself together, Justin.
A Little Mathematical Proof
Unknown, 2009-11-06
Did you know that if you take any non-negative integer, then subtract the sum of its digits, the answer will always be divisible by 9?
For example, today's date is 11/06. 1106-(1+1+6) = 1098, and 1098/9 = 122.
Curious why? Here's a more general proof [pdf], that the difference between a number and the sum of its digits (if written in base b) will always be divisible by (b-1).
For example, today's date is 11/06. 1106-(1+1+6) = 1098, and 1098/9 = 122.
Curious why? Here's a more general proof [pdf], that the difference between a number and the sum of its digits (if written in base b) will always be divisible by (b-1).
Michigan Updates
Unknown, 2009-09-25
Alright, I've finally decided to sit down and write in more detail about my Michigan experience.
Living in Ann Arbor is a little strange to me, as it's the first time I'm further removed from a large city. Being in Chicago for four years, visiting San Francisco, LA, and Seattle during the summers, have gotten me used to there being interesting "cultural" events around. I put cultural in quotes because there is of course an Ann Arbor culture, but what I'm talking about is museums and history and architecture. Seattle and San Francisco were great in this respect, where as Ann Arbor is a college town, and thus is dominated by eateries. The university and the town developed together, so only a few blocks from campus the streets become much quieter, and within 15 minutes drive it quickly turns into farmland. Although Detroit is only an hour or so away, I know of no quick/cheap way to get there, and even then I doubt there's much that would interest me. As a result most of my free time is spent reading or climbing, which is a saving grace of sorts. Michigan has a bouldering wall on South Campus, which is across the city from where I live, and so I commute there at least twice a week. It is also one of the few ways I've met people outside of engineering, as North Campus is dominated by engineers. So I've gotten a bit better at bouldering.
As for classes, I'm taking three, and I'll go through them below. As a final though, I will talk about my experience as a Graduate Student Instructor (TA)
Introduction to AI
I've already done a lot of the things on the syllabus, such as search algorithms, inference, and Bayesian networks. All this stuff, however, was done in different classes, and I later decided that this is because a Michigan semester is longer than the Northwestern quarter. I think I could have gotten an equivalency for the course if I wanted to, but I'm considering doing research with the professor, and it has been a while since I did most of the Good Old Fashioned AI (GOFAI) stuff, so I might as well sit in. So far the course has not been surprising, and I'm rather glad I'm in it, as it's my single "easy" class for the semester.
Machine Learning
Although I've also taken a machine learning course before, my previous work was very implementation biased. This course, on the other hand, is based entirely on statistics and linear algebra. I've only taken one course in both subjects, and linear algebra in my freshman year. The good thing is that I've been teaching linear algebra through the years (as it is part of the course I peer tutor), so the knowledge I retained from that is very helpful. To be honest, I'm not sure I will find the mathematical background to these methods helpful. I did read a paper where principal component analysis was used before the course covered it, so it was exciting to know a concrete example.
Computational Complexity
My background for this course is even stranger. Michigan has an undergraduate course on the theory of computation, which I have obviously never taken. Northwestern used to have a similar course, but the only place I've found it referenced was in the course catalog. So most of what I know about Turing Machines come from recreational reading. And it turns out that it was enough: books on Turing and Godel, together with what I picked up in my programming languages and compiler courses, gave me enough background to take the course. I like the course a lot; the professor has a nice way of putting everything in narrative and historical perspective. If I wasn't so interested in AI, theory would definitely be an area I would look into. A system of logic is just so... elegant.
Graduate Student Instructor (for Programming and Intro Data Structures)
Ah, teaching. I'm always surprised by how much teaching I've done already. I was involved with the GSW for all four years, one of them as a student. And I've done two summers of CTY. Still, I expected doing discussion sections and office hours to be different. But it wasn't; after the first day, when I think back to see what I could improve, I didn't see anything that I needed to adapt to the new format. Actually, this is now not entirely true - I think I need to do a better job of emphasizing why these concepts are important, in the world of computer science. It's much harder to keep a room of 30 college students than a room of 14 6th graders engaged, especially when you don't have much flexibility on what to teach.
Anyway, I'm definitely enjoying being a GSI. At least one student have told me that what I do is helpful, and several others have been asking me questions on computer science concepts outside of the course. Yeah. Now the hard part: keeping it up.
Living in Ann Arbor is a little strange to me, as it's the first time I'm further removed from a large city. Being in Chicago for four years, visiting San Francisco, LA, and Seattle during the summers, have gotten me used to there being interesting "cultural" events around. I put cultural in quotes because there is of course an Ann Arbor culture, but what I'm talking about is museums and history and architecture. Seattle and San Francisco were great in this respect, where as Ann Arbor is a college town, and thus is dominated by eateries. The university and the town developed together, so only a few blocks from campus the streets become much quieter, and within 15 minutes drive it quickly turns into farmland. Although Detroit is only an hour or so away, I know of no quick/cheap way to get there, and even then I doubt there's much that would interest me. As a result most of my free time is spent reading or climbing, which is a saving grace of sorts. Michigan has a bouldering wall on South Campus, which is across the city from where I live, and so I commute there at least twice a week. It is also one of the few ways I've met people outside of engineering, as North Campus is dominated by engineers. So I've gotten a bit better at bouldering.
As for classes, I'm taking three, and I'll go through them below. As a final though, I will talk about my experience as a Graduate Student Instructor (TA)
Introduction to AI
I've already done a lot of the things on the syllabus, such as search algorithms, inference, and Bayesian networks. All this stuff, however, was done in different classes, and I later decided that this is because a Michigan semester is longer than the Northwestern quarter. I think I could have gotten an equivalency for the course if I wanted to, but I'm considering doing research with the professor, and it has been a while since I did most of the Good Old Fashioned AI (GOFAI) stuff, so I might as well sit in. So far the course has not been surprising, and I'm rather glad I'm in it, as it's my single "easy" class for the semester.
Machine Learning
Although I've also taken a machine learning course before, my previous work was very implementation biased. This course, on the other hand, is based entirely on statistics and linear algebra. I've only taken one course in both subjects, and linear algebra in my freshman year. The good thing is that I've been teaching linear algebra through the years (as it is part of the course I peer tutor), so the knowledge I retained from that is very helpful. To be honest, I'm not sure I will find the mathematical background to these methods helpful. I did read a paper where principal component analysis was used before the course covered it, so it was exciting to know a concrete example.
Computational Complexity
My background for this course is even stranger. Michigan has an undergraduate course on the theory of computation, which I have obviously never taken. Northwestern used to have a similar course, but the only place I've found it referenced was in the course catalog. So most of what I know about Turing Machines come from recreational reading. And it turns out that it was enough: books on Turing and Godel, together with what I picked up in my programming languages and compiler courses, gave me enough background to take the course. I like the course a lot; the professor has a nice way of putting everything in narrative and historical perspective. If I wasn't so interested in AI, theory would definitely be an area I would look into. A system of logic is just so... elegant.
Graduate Student Instructor (for Programming and Intro Data Structures)
Ah, teaching. I'm always surprised by how much teaching I've done already. I was involved with the GSW for all four years, one of them as a student. And I've done two summers of CTY. Still, I expected doing discussion sections and office hours to be different. But it wasn't; after the first day, when I think back to see what I could improve, I didn't see anything that I needed to adapt to the new format. Actually, this is now not entirely true - I think I need to do a better job of emphasizing why these concepts are important, in the world of computer science. It's much harder to keep a room of 30 college students than a room of 14 6th graders engaged, especially when you don't have much flexibility on what to teach.
Anyway, I'm definitely enjoying being a GSI. At least one student have told me that what I do is helpful, and several others have been asking me questions on computer science concepts outside of the course. Yeah. Now the hard part: keeping it up.
Spiral Staircases
Unknown, 2009-09-09
The new Computer Science and Engineering building has a nice spiral staircase that rises prominently from the main hall. It connects all four floors of the building, and is the most convenient way to get directly up; there is at least one other staircase (probably more; I haven't found any emergency staircases), but that has significant horizontal translation.
I thought a spiral staircase was pretty cool when I first saw it, but as I'm using it more often, I realized how stupid an idea it really is.
The problem with a spiral staircase is that the steps are non-uniform. Since people's gait depends on their height, and their height is a random variable, people have preferences as to how wide a step should be. With a circular staircase, the steps are obviously longer towards the outside and shorter towards the inside. This means people can pick where they walk, right? Except, of course, when there's two way traffic, so people are forced to one side of the staircase. With normal stairs, moving to one side doesn't change your gait, and so you can continue walking. With spiral staircases though, you have to constantly adjust how far you're stretching your legs just to keep going.
Besides that, Michigan is going well. By virtue of it being a public university, the classes are quite a bit bigger than those at Northwestern, even for relatively obscure classes like machine learning. I think that's the only reason why professors seem a little more distant here than at NU. On the other hand, I have two discussion sections to lead next week, as well as however many office hours, and this is also with the largest number of students I've dealt with yet. It'll be fun.
I thought a spiral staircase was pretty cool when I first saw it, but as I'm using it more often, I realized how stupid an idea it really is.
The problem with a spiral staircase is that the steps are non-uniform. Since people's gait depends on their height, and their height is a random variable, people have preferences as to how wide a step should be. With a circular staircase, the steps are obviously longer towards the outside and shorter towards the inside. This means people can pick where they walk, right? Except, of course, when there's two way traffic, so people are forced to one side of the staircase. With normal stairs, moving to one side doesn't change your gait, and so you can continue walking. With spiral staircases though, you have to constantly adjust how far you're stretching your legs just to keep going.
Besides that, Michigan is going well. By virtue of it being a public university, the classes are quite a bit bigger than those at Northwestern, even for relatively obscure classes like machine learning. I think that's the only reason why professors seem a little more distant here than at NU. On the other hand, I have two discussion sections to lead next week, as well as however many office hours, and this is also with the largest number of students I've dealt with yet. It'll be fun.
Writing About Writing
Unknown, 2009-09-01
I have been writing recreationally for a while - I've been writing in my journal for close to 7.5 years, and this blog has been going for 2 years as well. Before that, I used to have a LiveJournal account, which was mostly used to keep my high school friends up to date with what I was doing. This blog stands out though, because it can be said that I'm doing a lot for a very small audience.
I recently read Paul Graham's essay on essays though, and I found it interesting that the word "essay" comes from the French verb/noun essayer/essai, meaning to try/an attempt. A lot of my blog posts are planned before hand. I have a running list of topics I want to write about, and while I find the time and mood to write them, I collect ideas and quotes in bullet-point form. Often times I don't actually know what I want to write, just want I want to write about. For example, I knew that I would do a post on The Fountainhead, but I didn't know what I want to say about it. Even for this short post, I'm not sure what my final point is, if I have one. Writing, then, is a way for me to figure out my own ideas. It's not just a tool for me to express my ideas to other people, but also for my ideas to become clearer in my head.
My friend Genia also wrote something about writing a little while back.
I thought it would be interesting to show the notes I have collected before writing this too. They're below:
I recently read Paul Graham's essay on essays though, and I found it interesting that the word "essay" comes from the French verb/noun essayer/essai, meaning to try/an attempt. A lot of my blog posts are planned before hand. I have a running list of topics I want to write about, and while I find the time and mood to write them, I collect ideas and quotes in bullet-point form. Often times I don't actually know what I want to write, just want I want to write about. For example, I knew that I would do a post on The Fountainhead, but I didn't know what I want to say about it. Even for this short post, I'm not sure what my final point is, if I have one. Writing, then, is a way for me to figure out my own ideas. It's not just a tool for me to express my ideas to other people, but also for my ideas to become clearer in my head.
My friend Genia also wrote something about writing a little while back.
I thought it would be interesting to show the notes I have collected before writing this too. They're below:
Paul Graham on essays
http://www.paulgraham.com/essay.html
the french essayer, to try
I have a goal, but I don't know how it turns out
I'm not sure what's the point I want to make in this essay
more to write thoughts down, to externalize and make concrete my thinking
to clarify ideas
http://petdinosaur.wordpress.com/2009/05/25/write-a-story-write-a-book/#comment-31
show notes for this essay
Subscribe to:
Posts
(
Atom
)