Blog Three: Making Meaning: POTs

Hillis’s (1998) ‘The Pattern on the Stone,’ introduces readers to the world of computer science. From examining the basics of programming (chapter three), defining and discussing basic algorithms and heuristics (chapter five), to touching on more advance subjects such as parallel computers (chapter seven), each chapter covers an entirely different area of computing. Chapters begin with the basics of each topic (i.e., defines what it is and how it relates to computing), and gets more complex (i.e., talking about its different aspects) as the chapter continues forth.

Because the book covered such a broad range of subjects I was unfamiliar with in fewer than two hundred pages, I felt most chapters were difficult and hard to follow. I would understand the beginning of each chapter; however as the chapter would go by I would find myself having to reread paragraphs (more so than textbooks in my 500 level psychology classes) to get a grasp at what the author was attempting to convey.  For example, during chapter six (Memory: Information and Secret Codes) I understood when Hillis (1998) was describing memory and its unit of measure (bits); however I hard difficulties in understanding when he was describing the various techniques (using bits) that can be used to measure memory.  I feel that if I had more time to reread the book again while taking notes, I would gain a better comprehension of the material and the fine details described within.

Overall, I was more bored and frustrated than anything when reading this textbook. Coming into this class, my knowledge regarding computer science was extremely minute; however I thought I would enjoy the class and that my interest in computer science would increase as time progressed.  Unfortunately, thus far my aspirations have not been met as I find most of the content confusing and uninteresting.  In regards to the book, I did enjoy how each chapter up until about halfway aligned with our in-class activities.  Although I didn’t understand everything the author was describing in each chapter, gaining the basic knowledge of the topic helped me complete each in class assignment (i.e., Turing Machine, algorithms).

There were two notable chapters that I had a high level of interest in. I thought the concepts and material within chapter seven (Speed: Parallel Computers) was interesting when describing how computer technology was/is progressively changing from sequential processing to each processor working together to solve a problem (similar to the human brain).  This was the rebuttal needed to disprove Amdahl’s law.  To further understand parallel computing, Blaise (2016) writes an in-depth article regarding the subject.  The article introduces parallel computing, implementations of its use today (e.g., finance and economic modeling, virtual reality, atmospheric pressure, weather readings), limits of parallel processing (e.g., mentions Amdahl’s law), what makes a good parallel processer (e.g., incorporating both fine and coarse grained detail), and the predicted future (e.g., ‘supercomputers’).  Blaise (2016) reiterated a lot of the information found within Hillis’s (1998) book, but includes imagery and a more current outlook on the subject.  On a final note regarding chapter seven, I thought it was interesting how close Hillis (1998) was at successfully predicting the future.  For example, Hillis made the prediction that the internet would eventually become connected to a number of household appliances (i.e., refrigerator; a prediction most computer scientists would have laughed at), which is something that is currently occurring in most middle and upper class households (I can log onto Face Book from my friend’s refrigerator).

Another chapter I found interesting was chapter nine (Beyond Engineering). Although the brain is much more complex and less prone for failure (i.e., neuroplasticity) than computers, the two are strongly related.  Technology has been on a path to become more like the human brain in that each part of the computer works together in the most efficient matter possible.  This is similar to the millions of neural networks that connect the parasympathetic and central nervous system; firing neurotransmitters between neurons (when sodium and potassium channels create an action potential) that cause our entire body to function as one.  Another aspect interesting in the chapter is how the advancement of computer technology is like Darwin’s survival of the fittest.  Because technology is greatly influenced by cultural and artificial selection, it is increasing at monumental speeds; however both technology and Darwin’s natural selection are influenced by the Baldwin Effect- the theory that social learning shapes evolution as much as evolution shapes social learning.

Overall this book definitely helped in dipping my feet into the water of computer science. Although I found it personally confusing, and there were many aspects I still don’t understand, I learned a significant amount throughout the novel.  As noted previously, learning was increased when we applied the book to in-class assignments; and I was able to understand the topics better when it was compared it to the human brain.  I would recommend this book to anyone who (like me) has a very limited knowledge regarding computer science.  I’d imagine there were many people in this class (for those that actually read it) who did not learn anything; and for those individuals I would recommend a more advanced textbook.

I don’t really have any questions that have been left unanswered. I read the book, but I feel that if I took a test on it I would not perform well as (previously noted) there was too much to comprehend in only two hundred words; thus I would need to reread and takes extensive notes on it.  Having said that, the most significant thing about the book was it’s ability to cover such a broad range of topics.  Although I may not know the fine details about any specific topic, I now know what computer science entails and the facets the lie within it.

References

Hillis, D. W. (1998). The pattern on the stone: The simple ideas that make computers work. New York, NY: Basic Books.

Blaise, B. (2016). Introduction to parallel computing. Livermore Computing Center. Retrieved from https://computing.llnl.gov/tutorials/parallel_comp/

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