Parallels

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The first time I heard of computer programming, I thought it was teaching a computer what to think. I thought it meant how to get computers to do certain tasks and create different types of programs. While that is partially true, what I was thinking was only a small subset of what computer programming actually is. The basis of computer programming is telling the computer what to do. What you want it to do is up to you. You can automate processes (such as assigning groups), you can solve complex equations (calculators), you can program robots to move and analyze things (Mars rovers), etc. In the most general terms, you are instructing a machine to do a certain task, and it returns a certain output, usually accomplishing the task.

When my grandfather had a stroke, I had just completed my 7th grade. I wasn’t very close with him, but it still came as a shock to me. For the next few years I went to India but I never really conversed with him that much. I usually helped him walk down the stairs and walk around the base of the apartment, but I didn’t start talking to him until my sophomore year. When he came to the US, he was sitting bored in one corner of the house for extended periods of time. There wasn’t much my grandmother could do either, so she resigned to watching TV and going on walks. I decided to go and talk to him. I remember my dad mentioned that he was a Math Professor, so I brought my Pre-Calc textbook and asked him to do five problems. I wanted to see if he still remembered this stuff or if I could reteach it to him.

He struggled with the first few problems. I aided him along the way, asking him if he remembered specific things such as trig identities and factoring equations. As he got more comfortable, I figured he could do more. I gave him a few more problems but after a while I had to call it a night. The next day I went and asked him to try a few more problems, all similar to the ones I gave him the previous day. However, he looked at the problems with a blank expression on his face. I pulled up a chair and aided him again, and he was able to formulaically do the next few.

The real test was when I gave him a word problem. In that specific problem, it was just a similar equation put into word form. I wanted to know if he could convert the question into the previous format and then solve it methodically, just as he had done on the previous problem. However he was unable to understand the concept! I stopped and realized that he hadn’t actually relearned anything. He was simply memorizing formulas on how to take the factors of an equation or how to implement a trig identity.

I figured that this was a similar problem in trying to get our computer to do our work for us. When we program a computer, we expect it to have implicit obedience to its user. We don’t program it with a mind of its own, it simply listens to whatever command the user enters and outputs whatever it is told to produce. Therefore we can never have true artificial intelligence because it seems as though the robot can never have a mind of its own.

I went back to working with my grandpa on some math problems, but this time I didn’t guide him by reminding him on which formulas he needed to use. Instead I just had him sit there and stare at the problem. When he started telling me to write the next step down for him, I asked him to tell me what that step was. He finally gave in and started thinking about it on his own. He would remember what the formulas were, and even though he messed up sometimes, like with a positive instead of a negative sign, he was still able to figure out the solution on his own. He started showing signs of improvement in his work. I gave him a few more word problems and he understood how to frame them into equations.

So what if “real” artificial intelligence doesn’t work out? Does it really matter if we know that the robot has been programmed one way or another rather than learn things through trial and error? The important part is that the machine can understand how to process different kinds information and produce a good outcome. And the fact that machines can process and run through simple calculations much faster than innate human capabilities means that computers will learn faster than us.

People say that we’ve reached the computer age, where everyone should be computer literate. However, that age will soon pass, and we’ll approach the age where everyone should know how to teach, because we’re going to be teaching computers to do things for us.

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Moonrise Kingdom


Back in the 1950’s, conformity was key. In the movie Moonrise Kingdom, the two children Sam and Suzy were allowed only a certain amount of leeway to do what they wanted. Other than that, they were expected to follow the norms of society and to simply do what they were told. Sam and Suzy are seeking an escape from all of the norms and rules of the main island. There, everyone is expected to behave in a certain way and no one is allowed to feel any emotion.

Moonrise Kingdom is a great movie that encapsulates the motifs of the 1950’s. However, is it still applicable now? Since then there have been revolutionary ideas that have completely wrecked the norms, such as the civil rights movements and the hippie movements. There has been a complete loss of faith in the US government, in the cases of both Richard Nixon and George Bush Jr.

Do we still expect kids to conform to society’s norms? To some extent, yes. High school is symbolized by conformity; if you don’t follow certain norms, you are judged. But for the past decade or so, people in general have been trying to open their minds to others who behave or act differently. The whole atmosphere has changed, where there are support groups and organizations that accept people for who they are rather than trying to change them into something that society wants.

It is not perfect yet. There are still so many more things that we can do to be more accepting of other people. However the first step to solving a problem is recognizing that there is one. The fact that we have started accepting people who don’t fit the norm is a sign that we have recognized this problem.

Music as a Language

http://www.theatlantic.com/health/archive/2014/02/how-brains-see-music-as-language/283936/

This article explores a new avenue of the music-brain relationship. It states that people listen and respond to music as a language, much in the same way people hold conversations. It says that music and spoken language impact the brain in a similar fashion. The way that jazz ensembles play improvisations so well with nothing but the previous piece of music to go off of is astounding. However, this article explores the notion that the jazz artists hear the previous part of the song and try to generate a response based on some guidelines and play it back as part of the song. This is an interesting article on how the brain works!

Climbing

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This is one of the most incredible videos I have seen since Felix Baumgartner jumped off of a spacecraft and dove to earth.

There is something that has always perplexed me about videos like this. While watching them climb up these incredible heights, my palms start to get sweaty. I feel really scared and excited at the same time. I don’t know what it is, but for some reason, I just can’t stop watching. Even though I know that there is a 99.99% chance that this video is real and they make it to the top, I still feel the adrenaline rush to my head.

I feel as though there is some interconnectedness within the human species. When I was watching them climb up to the top of the tower, I was rooting for them to succeed. Every time they didn’t know which step to take next, I suddenly felt a nervous tingle. Whenever there was a slight misstep, I thought that maybe he was going to fall and I held my breath.

I thought that I felt the exact same feelings that the man was feeling, obviously to a much lesser degree. Even when I know the outcome, watching it happen still gives me the thrills that I think those men felt as they were climbing up that giant tower.

Music

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It’s so hard for me to listen to music that I don’t know. Every time I listen to a song, I think about a moment that love, something that I have experienced, something that I know. When I listen to Perfect Day by the Constellations, I think of the first time I watched the TV show, Suits. When I listen to Iris by the Goo Goo Dolls, I think of my last two DECA conferences, where even though I didn’t do as well as I thought, I really enjoyed my time with my friends. When I listen to Hotel California by the Eagles, I think of the millions of times that I struggled playing the chords on my guitar.

Music adds something to people. Every single song that I listen to puts me in a mood that I remember the last time I listened to it. It brings back some memories for me that I couldn’t recall otherwise. I listen to music because I love to reminisce in the past.

I don’t like certain songs. Not because they bring bad memories, but because they don’t make me feel anything. I can’t stand listening to rap, mainly because I don’t feel anything. It’s not that rap is bad, but it’s just that the words are simply words, they have no melody. That just doesn’t cut it for me.

Maybe it’s because I love to sing. Ever since I was in elementary school I have had a passion for singing. Whenever I have no means of listening to my iPod or phone, I start singing, usually quietly to myself. I usually like to sing Disney songs, mainly because they have a great melody, they remind me of my childhood, and they are easier to sing.

I have a favorite song every few months. Over the summer I was obsessed with Fix You by Coldplay. Whenever I listen to that song, I always feel linked to my experiences at Stanford and Carnegie Mellon. Over Thanksgiving break, I was into Happy Together by the Turtles. It was a song that used to come in all the advertisements, and I just loved the changes in tempo. Recently, like I said earlier, I have been engrossed in Iris by the Goo Goo Dolls.

I love songs that make you feel a certain way and have a certain mood. Regardless of what I am feeling before, I always feel different after I listen to one of my songs.

Surprise

You can run a scenario through your mind a thousand times, yet there is never any expectation of what is going to happen. You can assume that most human beings are going to behave rationally, but eventually you will come to realize that everyone is self-interested. And even when people are self interested, they have thousands of avenues, involving both instant gratification and delaying for a greater reward. 

Who knows what the other person is actually thinking? Who knows what we are thinking? A decision is made in that split second or hour or week or however long. That decision is based on a few factors, all of which have to do with the current state of the object or character. If say a person lost a lot of money in the stock market and got offered to make some shady deals the very next day, he might take up the job simply because he feels as though all that money may be gone forever.

Simply put, nothing like that is commercially available today. I agree with Dr. Douglas Hofstadter’s contention that Siri and Watson are not real AI. They are incredibly advanced search algorithms, but they can’t comprehend what they are comparing. However, to what extent will we be able to program some smart device that can start to think on its own?

Creating a neural network in a robot seems nearly impossible. People have devoted their entire life to building a neural network with no success. To some extent there has to be an algorithm or a heuristic process that weeds out the information. If you think about it, there is absolutely no way to program a computer to think like a human because deep down, the computer is only limited to the scope of a human mind, and will never be able to perfectly replicate it. The only way that a robot would be able to return information will be by looking through a database of previous text and figure out a response. It may tell the difference between a noun and a verb, but it will never be able to actually think how to put sentences together. It will only be programmed to do so.

So are projects like Siri and robots like Watson good enough? Obviously not, we will keep working towards building a smart AI that can process words and think on its own. However, robots won’t have the ability to think on their own. Robots won’t be able to surprise humans, because after all, we are the ones that will program their abilities. We will program to string certain words together and follow certain sentence structure. Maybe they will listen to others talk and store certain sentence structures in a database. Maybe it will use that structure with different words and realize that it doesn’t work.

Soon enough there will be AI that run so smoothly that it seems like they can think on their own. But underlying all those million lines of code is the programmer who coded, not taught it, how to think.

http://www.popularmechanics.com/technology/engineering/news/why-watson-and-siri-are-not-real-ai-16477207

The Catcher in the Rye

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I know book reviews aren’t my thing, but this book was very effective in conveying a message.

The smartest people in the world are those who can form their own opinions quickly based on experience and sound reasoning. There are, of course, ‘phonies’ who steal others’ opinions and use it as their own. So how can we tell the difference? The Catcher in the Rye by J.D. Salinger explores this topic thoroughly, taking the reader through the vantage point of Holden Caulfield, a juvenile teenager trying to find his way in the world. Of all the books I read in high school, this stood out to me the most.

I spent the majority of my life using others opinions and ideas to get by in life; all things that kids are supposed to do. Just before I read Salinger’s novel the first time, I had started noticing myself doing that. After reading the novel, and seeing how critical Holden was of people who did that, I wanted to change. For that, I had to understand how I formed my opinions.

I realized that whenever I read a new article, my outlook on that certain topic changed. My opinion was subject to the prejudice of the author. I contemplated on how I was supposed to form my own thoughts, because everything that I know was based on something someone else has told me. To try and understand, I went back to that book.

I realized that opinions still are based on what we know, but the smartest people are those who stand by their opinions even when conflicting ideas are presented to them. They seem to form their opinions while young, and modify them as they experience life. These are the most morally stable and mentally sound people, and I strive to be like them. Catcher in the Rye opened my eyes to a different me.

Graphing Calc Class

Screen Shot of Graphing Calc

In my calculus BC class, we had the option of taking time out of class to go work on building a calculator that can graph original functions and their derivatives. The entire process would have taken a lot less time if I didn’t have to write my own parser on converting a string to an equation, but nonetheless, it was worth the whole work because I was able to overcome a very difficult challenge in my short computer science career.

The Parser converted infix notation, the one that we are typically used to, to postfix notation and then solved the entire thing. Infix notation is where all the operators are in between the operands, and the equation uses parenthesis to define its orders of operation. In postfix notation, the operands are both next to each other and the operator comes after the two variables that it operates on. Depending on the position of the operator, it is easy to determine how the order of operations works in the system.

To set up the graphics program, I used the open source Stanford ACM graphics library. For me, it facilitated the process because I had been using it for most of the summer, and it made the entire process much smoother for me. I had to create a backdrop and draw my own axes, and then create a separate panel on the side where the user can input the function and set the left and right bounds (the screen will always remain a square). Then I let the user define their choice of color using an RGB style.

Plotting the points took an entire algorithm to shift the points onto the screen, but eventually after trial and error, it came out well. I used multiple classes that each handled different aspects of the process, and I was able to completely graph both the first and second derivative by taking very small intervals and finding the slope of each curve.

There still are a few bugs that I need to work out. First, each general function, such as sin(x+2) has its own way of solving within the parenthesis. Instead, the function could simply be recursive and return a numerical value within the function and then solve the function of the number. Next, the algorithm doesn’t continue after the function runs a first time.

There are also ways to make the calculator more aesthetically appealing. However, this is a great first step towards building useful applications in computer science for years to come. And to keep up with the theme, I now am continuing working on my two projects from Carnegie Mellon.

Reading Directions

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Reading directions is hard. Writing the code for Reverse Polish Notation is even harder.

For my Calculus class, I have to write the code for a graphing calculator that can take the derivative of an equation, much like the one on Wolfram, but a lot harder. I also thought it had to solve equations, which made my life infinitely more complicated. Until I found out that I don’t.

I started writing the code for RPN around mid september. I didn’t know how I was going to do it, and I had no clue what RPN was in the first place. Soon I learned it and the Shunting Yard algorithms off the internet, and finally found a way to solve my problem. As it turned out, there was another problem. The directions never asked me to write a code that can solve equations. All it wanted to do was graph.

So now I’m sitting on top of a fat RPN code which works, but doesn’t solve my problem. But I don’t really care if I can’t use it. I feel really good being able to write it. This is the first hard piece of code that has a lot of practical use. I guess I see the glass as half full.

Topsy Turvy

 

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Recently I have been surfing the web for the coolest thing I could find in the topic of data mining. I don’t know if this is the coolest, but it is definitely up there!

http://topsy.com/

Topsy seems like its the worlds biggest fan of twitter. But in reality, it’s much more than that. I think that topsy has taken one giant step forward in the world of data mining and data analysis, one very different from that of Palantir‘s.

Topsy has every single tweet posted, not only in the last month, and not only in the US, but every tweet ever in the world. It would seem insane for most people, but to me it seems like a priceless business. By purchasing their product, you not only have access to all the tweets, but you can analyze what hashtags people are posting and which locations are these most prevalent. You can analyze social groups, determine what age group are your target audience, and figure out what works best for your campaign.

All of this is being done online, with topsy’s user friendly interface. My advice is to look into this software right away. It’s absolutely brilliant and poses a new frontier for marketing and advertising.