Firstly, I seem to be always criticizing courses and programmes. I would like to remind everyone, that I am not a critic, neither am I a pessimist. Remember how I said that orientation, some level camps and all were rather disappointing? Well, it isn't really my fault that they are bad and neither would I like to lie about it, even to myself, just to appease optimistic laughing bouncing bunnies who thinks that everything in existence is lovely like a rainbow.
The truth is, the world is in a mess and no course would be good unless the organizing committees are clear about their objectives and are sincere in carrying it out for the participants, rather than for other advantages. In addition, learning to accept the truth is important too, even if it's against you. So when you see 'leaders' in 'leadership camps' drooling off to sleep as the speaker drones on about the importance of trust and teamwork and respect, you know what to blame.
Perhaps others think that the course was acceptable, but I strongly believe that it could be improved to decrease time-wastage on the participant's behalf.
At first I was rather enthusiastic, I mean, "Haha! All my friends only get to attend ONE YDSP module but I get to attend TWO!" And I was excited about it, but now I think that I have wasted 3 days of my precious holiday, whose days are seeping away like sand among my fingers...
Nevertheless, there are quite a few things that I have learnt.
Day One:
Introduction to AI. Couldn't wait for lunch. Then we hard-coded a tic-tac-toe game, which was rather elementary considering that we did not even code the programme, we just inserted mono-level conditional statements into a notepad file. Fair enough, considering that it was an introductory activity. Next up, was a lecture about machine learning. Personally, I feel that for a machine to truly learn, it requires creativity, and pattern recognition ability, like how a newborn baby picks up language. You show the object to him, and say the word. Consequently, he will associate the two together; that's pattern recognition for you. Creativity is no less important. To advance, the machine has to be able to create new ideas, then test them out, otherwise, it is not doing much, other than following instructions from the programmer. Alright, instilling a machine with creativity is a rather long shot...
Again, I don't find the need for a machine to be that intelligent. All humans need for a machine is to follow instructions to make tasks easier for them, not taking a life on its own. The latter can be done with another human, and unless you are a lonely person who doesn't have any friends to play a computer game with you, machines do not have to be THAT intelligent.
Their vegetarian lunch set was horrible.
We went to NUS in the afternoon. Listened to a few people talk, but the content was minimal. They were mostly presenting about games, like how an AI can work together with human in a co-operative game. Then a orchestra conducting game, which had totally nothing to do with AI was shown to us.
Day 2:
Dad took me to RGS today. Heavy rain, traffic jams, stevens road was flooded to the kerb. I was late by a quarter hour. When I entered, the lecturer was talking about the brain. Turns out that the whole session was about the structure and functionalities about the brain, and how it inspired certain cognotive architectures to be designed. Unfortunately, they were not well elaborated on, which quite defeats the whole purpose of the lecture about the brain.
I disagree on one point however, that the amount of neurons in the brain does not affect intelligence. In craniates, there is a relationship between the ratio of brain mass to total body mass and the intelligence of the organism. Therefore, for animals of the same mass, the one with larger brain mass is more intelligent. The lecturer said that the architecture of the brain was more important, because an elephant has a larger brain and is yet not more intelligent than human, and because the computational power of the human brain and the modern computer is similar. However over here, we are comparing two things, inorganic computer circuit boards and the organic brain, so how is it a fair statement to say that number of neurons does not affect the intelligence of an organism. I think it does.
Next up, introduction to robotics, and applications of AI. It was quite a bit of a repeat to what I learnt when playing with lego mindstorms since primary school, and in DSO office with Jk. Then they talked a little about automated vehicles created to compete in DARPA's challenges, followed by a presentation about the linguistic abilities of AI, which would have been interesting if I understood it, as it included a lot of probability notation, and our school have not touched much about it(other t
Their vegetarian lunch set was horrible.
but the agar was good.
We went to NTU this time. By now, I was getting restless with this AI course, and refused to wake up when we reached NTU even though I'm aware that we are there until Jk called me a few more times. Yes, I can be rather (insert adjective that describes the character of not waking up and waiting for someone to wake you up even if you know that you will have to wake up eventually because you have to alight the bus) at times.
The guide brought us to visit the library to watch students studying, which amusingly made me associate this to a zoo tour, by seeing students discussing and learning in 'cages'. Then we went to the top floor and looked at the books, which was really demoralizing. Upon opening the mathematical journals, I didn't understand what the questions posed meant, or what the english word even meant, let alone understanding the journal. Number theory and topology, to great fields of mathematics that I have never touched and learned in my life.
So after school reopens, I hope to get more mathematics books from the school library and read up. If elementary calculus wasn't that hard to grasp, learning topology and basic number theory wouldn't be impossible.
Then we hopped into the world of advertising. We went to a certain computer lab, where the students/staff at NTU made several presentations on 'why NTU school of computer engineering' is the best choice for us. Then they opened a few computer applications done as projects by students and described them and let us try them, and finally ending the whole session with a Q & A about life in NTU computer engineering faculty...
Day 3
Two mini projects today. First one was a "programming" project. We had to make the bulky robot follow the line and shoot down its target. "Programming" because everything from the logic to algorithm was already done for us. So all we had to do was tweak the parameters...
Then they claimed that it was because they didn't want to do things of too high a standard, in order to cater to every student's needs. But again, if we even got a chance to attend this module, we probably wouldn't be that dumb as to find entering parameters a great programming challenge. And I remember hearing that these YDSP modules were of a high standard, which we would not be able to follow unless we attended every session and pay attention...
Their vegetarian lunch set was horrible.
Second mini project was designing an AI. My acceleration in socializing was pretty low, so I didn't talk much. We designed an AI for a game where you add matchsticks to a grid and get points for enclosing a box. Jk's friend (Not sure what's his name) and I set up a co ordinate system and thought of the code, which was unfortunately, not needed.
For the rest of the time, Jk's friend showed me this mathematical game called conway's game of life, in which there is a grid made of cells, and with a certain set of rules(2 or 3 surrounding cells cause central cell to survive, 3 surrounding causes activation of central cell, 0 and 1 surrounding cells cause loneliness and death of central cell, and more than 3 causes overcrowding and death of central cell). So basically with this set of rules, and a starting configuration, the cells manifest or die out into different patterns. When the grid gets big and cells arrange into complicated patterns, many interesting phenomena happen, like they start oscillating, and they travel as a pack, or grow without limit.
http://www.math.com/students/wonders/life/life.html
Quoting the website:
Why is Life So Interesting?
Life is one of the simplest examples of what is sometimes called "emergent complexity" or "self-organizing systems." This subject area has captured the attention of scientists and mathematicians in diverse fields. It is the study of how elaborate patterns and behaviors can emerge from very simple rules. It helps us understand, for example, how the petals on a rose or the stripes on a zebra can arise from a tissue of living cells growing together. It can even help us understand the diversity of life that has evolved on earth.
In Life, as in nature, we observe many fascinating phenomena. Nature, however, is complicated and we aren't sure of all the rules. The game of Life lets us observe a system where we know all the rules. Just like we can study simple animals (like worms) to discover things about more complex animals (like humans), people can study the game of Life to learn about patterns and behaviors in more complex systems.
The rules described above are all that's needed to discover anything there is to know about Life, and we'll see that this includes a great deal. Unlike most computer games, the rules themselves create the patterns, rather than programmers creating a complex set of game situations.
How Complex Can Life Get?
A computer can be built inside the Life "universe". Space does not permit a detailed description, but you can find much more information in some of the references given at the bottom. Briefly, streams of gliders and spaceships can be used to send information just as electrical signals are used to send information in a physical computer. These streams of gliders can react in a way to perform all of the logical functions on which a modern computer is based. It would be very impractical to build a computer this way, but given a large enough Life pattern and enough time, we could run any program that runs on a computer. Several interesting special-purpose computers have been constructed as Life, including one that outputs the prime numbers.
A universal constructor can even be built. This is a pattern that can take a blueprint for some other Life pattern (or its own) and build that pattern. No one has built this yet, since it would be very large, but it has been shown to be possible. This means that Life patterns could exist that reproduce themselves. They could even modify their blueprints just as living things combine and mutate their genes. Who can say what would develop in a large enough universe of reproducing Life patterns?
What is Life Good For?
Studying the patterns of Life can result in discoveries in other areas of math and science.
The behavior of cells or animals can be better understood using simple rules. Behavior that seems intelligent, such as we see in ant colonies might just be simple rules that we don't understand yet. Take a look at this simulation of termites piling up woodchips. There are only 2 rules in this system, and yet, a seemingly "intelligent" pattern emerges. What does this say about the nature of intelligence?
Traffic problems might be solved by analyzing them with the mathematical tools learned from these types of simulations.
Computer viruses are also examples of cellular automata. Finding the cure for computer viruses could be hidden in the patterns of this simple game.
Human diseases might be cured if we could better understand why cells live and die.
Exploring the galaxies would be easier if machines could be invented that could build themselves. Imagine sending a probe to Mars that could build a copy of itself. Although this is theoretically possible, it hasn't been invented yet!
Is Life Alive?
Would living creatures evolve in a sufficiently large Life universe if we waited long enough? We can see that Life, simple as it is to describe, exhibits much of the complexity of our own universe. It is intriguing to ask what would happen in an infinitely large Life space seeded with random patterns. It seems that likely that complexity would emerge beyond what we can see when we watch Life on a computer. Even in our own universe, there is a huge difference between what we know about natural history and what we can observe on a human time frame.
On the other hand, Life has only two dimensions, unlike our own universe, and that is a severe limitation. There are other properties of Life -- the tendency to stabilize locally into oscillators -- that may make it an unlikely place for living things to develop. The answer to this question remains unknown, but Life illustrates at a simplified level the kinds of evolutionary forces that we witness in our own universe.
And I tried it and it was not exactly fun to play with, but it was rather fascinating, when you look at the macroscopic effect of all the millions of cells interacting, then zooming down to the cellular level, and knowing that all these happen due to a few simple rules...Back to the topic.
During the presentation, we missed out on several good, but perhaps irrelevant, points which was quite a pity. Ultimately, those groups that won were those which used ideas and concepts from previous lectures, like linguistic ability, machine learning...etc, no matter how impractical, lame, unoriginal and easy talk they were.
In the end consolation prize winners got a 10 dollar MPH voucher, each. While the top prize was 50 dollar MPH voucher each. Seems like they have got a lot of funding.
Conclusion:
Didn't learn much, but it was quite an exposure to the world of AI, which is good, just that i don't find it that helpful in our programming project.
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