I want to think quickly. I want to be able to read books as fast as I can while comprehending everything. How do I learn to do this? Well, I need to train my brain to process information more quickly. This is tricky because there are many different types of information. To understand information, I need to develop a practical model to understand how information is processed.
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The simplest type of information comes from direct sensation. We see an object and then we identify it with a term. Nouns are the easiest to categorize. Action verbs come next. We observe actions performed by and on objects so we develop terms for them. This requires prerequisite nouns. Adjectives, intransitive verbs, helping verbs, adverbs, prepositions, and conjunctions all follow from this.
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The words that come from direct sensation combine to form ideas. Ideas require subjects and predicates like a regular sentence. Ideas reveal additional information about a certain term. There's the term 'dog'. There's the idea 'the dog is outside'. Simple enough. Ideas often convey why certain terms are important. While there are often very few words to describe a specific object, there are many words one can use to convey an idea.
Tuesday, August 17, 2010
Saturday, August 14, 2010
To leave behind
When one's work is eventually destroyed and their body is long dead, what is left of him? One's work creates works so no one is ever completely destroyed. When a man dies, he lives on in thoughts, memories, and works that reveal the information that comprised him. When these works thoughts, memories, and works fade, they only fade to leave a legacy of themselves. This infinitude of legacies may be the only afterlife we have, but it's the only afterlife we need.
Saturday, January 9, 2010
Algorithms, Algorithms, and...recursion?
The ultimate goal in math, science, and really all of learning should be to develop a comprehensive theory that connects and explains all of science in such a way that one who knows the theory can derive all other formulas that fall under the rubric of Physics and Chemistry. Think about it kids, you'll just have to learn one theory for class and you'll be able to wing and improvise your way to perfect scores. How do we come up with such a theory?
Science ultimately asks one question, "what is the cause of measurable phenomena?". This gets garbled into a whole bunch of other stimulating questions such as "Why won't my TV work?", "Why isn't there anything interesting on TV?", and "How come Twitter isn't working?". Oh, my favorite one of all time is "How come I'm on fire?". Such inquiries inevitably result in the developments of algorithms to build a TV, program Twitter, or start/stop a fire.
That's boring enough, but it gets interesting when you think about how we come up with those algorithms. Naturally, we examine how effectively the algorithm functions. What if it doesn't function properly? Obviously, we keep trying solutions. However, we don't just try solutions at random. That is, we don't arbitrarily test algorithms. We come up with procedures to find algorithms for specific problems.
For example, take the equation x^2+5x+8. We apply an algorithm(the quadratic formula) to solve for x. To derive the quadratic formula, we apply other algorithms! One usually either applies the algorithm to complete the square or Lagrange resolvents of Galois theory to derive the quadratic formula. Either way, one uses algorithms to find algorithms to find algorithms and so forth. It is the goal of all empirical and deductive learning to find a fundamental cause to everything to facilitate the development of an immensely complex procedure to potentially find any value of any phenomenon in existence. Link everything to a common cause then one can develop a universal algorithm. This leads us to better understand what society once called, and this blogger still calls, God.
This holds as we try to master and perfect ourselves to the highest ideals. Find patterns to find patterns to find patterns...Find patterns to refine patterns to find patterns to refine patterns. Confusing, isn't it? I take comfort in its complexity to know that there's always HOPE.
Science ultimately asks one question, "what is the cause of measurable phenomena?". This gets garbled into a whole bunch of other stimulating questions such as "Why won't my TV work?", "Why isn't there anything interesting on TV?", and "How come Twitter isn't working?". Oh, my favorite one of all time is "How come I'm on fire?". Such inquiries inevitably result in the developments of algorithms to build a TV, program Twitter, or start/stop a fire.
That's boring enough, but it gets interesting when you think about how we come up with those algorithms. Naturally, we examine how effectively the algorithm functions. What if it doesn't function properly? Obviously, we keep trying solutions. However, we don't just try solutions at random. That is, we don't arbitrarily test algorithms. We come up with procedures to find algorithms for specific problems.
For example, take the equation x^2+5x+8. We apply an algorithm(the quadratic formula) to solve for x. To derive the quadratic formula, we apply other algorithms! One usually either applies the algorithm to complete the square or Lagrange resolvents of Galois theory to derive the quadratic formula. Either way, one uses algorithms to find algorithms to find algorithms and so forth. It is the goal of all empirical and deductive learning to find a fundamental cause to everything to facilitate the development of an immensely complex procedure to potentially find any value of any phenomenon in existence. Link everything to a common cause then one can develop a universal algorithm. This leads us to better understand what society once called, and this blogger still calls, God.
This holds as we try to master and perfect ourselves to the highest ideals. Find patterns to find patterns to find patterns...Find patterns to refine patterns to find patterns to refine patterns. Confusing, isn't it? I take comfort in its complexity to know that there's always HOPE.