As most of America knows, our financial system started to implode in the fall of 2008. At that time, Ashley and I had a small one year old girl, a mortgage, and a car payment. While we were not struggling by any sense of the imagination, I felt like we were carry too much debt and that we could do better with budgeting our expenses. So, as I am wont to do, I began to gather information and develop a plan. One site I began to read fairly regularly was The Simple Dollar. While he posts a good bit of information on how to get your finances in order, I found that I tended to use his stories more as inspiration than as practical steps to follow. One book that I read that had a profound impact on how I look at our finances is Dave Ramsey’s The Total Money Makeover: A Proven Plan for Financial Fitness
. After I finished reading it, I immediately handed the book to Ashley and told her that she had to read it. Shortly thereafter, we both set down and began to follow Dave’s strategy for reducing our debt and increasing our financial stability.
After a year of work, we finally managed to increase our savings to a fairly comfortable mark of six months worth of expenses and eliminated all non-mortgage debt. Additionally, we eradicated the use of all of our credit cards and have migrated to a cash-only household (well, cash and debit cards) — we have not used any form of credit in around two years. Now, we are well on our way towards paying off our mortgage in another four years and have been able to expend a bit of capital towards household improvements. As we are doing this, I have been looking towards the future. The Millionaire Next Door
has had an effect on how we are planning for the future. My hope is for Ashley and I to be PAW for the next fifteen to twenty years or so (just long enough to get Emily into college) and then to start looking towards my next career — maybe starting that business that I have been dreaming about.
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Business and marketing — those are funny subjects for an engineer to study, aren’t they? As I see it, though, it is my duty to try and gain some business sense. Understanding how the product I am developing fits into the broader marketplace allows me better develop the product. My prior employer thought so, since the graduate school curriculum that they endorsed had courses in Strategic Management and in Cost Accounting.
In the far future, I will probably start my own business. I am not sure whether I will pursue some kind of engineering company or branch out into a completely different field. I just know that, some day, I want a business all of my own. Until then, the business reading that I do is for my company and my own edification.
What do I study? Mostly, I read weblogs such as Seth Godin, Pamela Slim, and Michael Lopp. I also tend to devour books on various topics such as Made to Stick: Why Some Ideas Survive and Others Die
and Made to Stick: Why Some Ideas Survive and Others Die (yes, I know me reading books different topics is a huge shock — I like to read, get over it).
If you know of any other really good business weblogs, please let me know in the comments. I am always looking for more information to consume.
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Yes, another Computer Science related Jack of All Trades post. I promise that this is the last C.S. related post for a while. Why do I like studying algorithms? Probably the same reason that I like studying Mathematics; both are very precisely defined and have interesting characteristics for study, but no matter how much you learn, there is always more to discover. Recently, I read an article in ACM Queue called You’re Doing it Wrong that discussed performance trade-offs between two algorithms and how, given the traditional understanding of computing systems, one algorithm clearly performed better. However, under real-world conditions with modern processors, secondary effects caused the other algorithm to perform better in this particular use-case. This article has gotten me thinking about how particular algorithms are chosen for a task and how much effort should be put in to choosing the appropriate algorithm.
In my studies, I am of course consulting the honorable Knuth and his venerable The Art of Computer Programming. It is slow going; if I ever finish it, I will probably be an aged man. However, I will know more about Algorithms that most people should. I am not sure that this study has any practical consideration outside of my field of interest other than training my mind to think logically. Maybe that is reason enough to study it.
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Of all the subjects in Computer Science to grab my interest, it is the study of programming languages that holds a place closest to my heart. Honestly, I am not entirely sure why. It probably hearkens back to my AP Computer Science course in high school. The particular assignment is not really important, but the class was allowed to implement it in either C or Pascal (the two languages being taught at MSMS at the time). After everyone turned in their assignments, which took several pages of code to accomplish, the professor showed us his implementation is a weird little language called Lisp. His version of the program took around 3/4 of a page &mash; probably 1/4 of the length of any of out versions. Seeing the simplicity of the code made me want to understand what it was that was unique about Lisp and sent me off to the library to get whatever I could about the strange little language.
Fast forward 13 years. Now, I have done a bit of serious programming in C and C++ and dabbled in Lisp, Forth, Python, SmallTalk, and Haskell. Each of these languages has their own pros and cons, but learning about their differences and their implementations fascinate me. So, I have bought several books on language (and compiler) implementation and have allowed my math studies to be directed towards the theory of Programming Languages. I lurk a good bit on Lambda the Ultimate, a programming languages weblog. I have played around with some simple implementations of Lisp and Forth clones and want to ultimate build one of those two on a machine from the ground up &mash; that is, make the language implementation into the Operating System for the computer, like it was in the old days.
I am interested in making programming more accessible to everyone. I am not sure what form that will take, but I believe that it come out of the concept I mentioned in my AI post about Fuzzy Literate Programming, something that does not yet exists but I bank will occur in the future.
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Artificial Intelligence has fascinated me almost as long as computers have fascinated me. I do not know whether it was C-3PO and R2-D2 from Star Wars, the ship’s computer from Star Trek, or Johnny Five from Short Circuit that interested me in AI, but it was surely one of them. Actually, most of those characters also got me interested in robotics as well. The thought that we (read: humans) could build something that could interact with us like one of us is very appealing to me. While I have often dreamed about AI, I have never really had a good opportunity to study it in depth. So, I am attempting to correct that. I have, sitting on my book shelf, The Emperor’s New Mind (Roger Penrose), The Society of Mind (Marvin Minsky), Programming Collective Intelligence, and AI: A Modern Approach.
Getting on a bit of a soapbox, though, I do not believe that true artificial intelligence or artificial consciousness is something that we, as a society, want or need at the moment. Putting aside doomsday movies like the Terminator, Wargames, and Colossus: The Forbin Project, how would we as a society deal with a machine that cam up with, and stated, “I think, therefore I am”, à la Bicentennial Man? Could we ethically cripple a machine that is capable of thinking by forcing it to obey our commands through something such as Asimov’s First Law of Robotics? Luckily, I do not believe that computer scientists are any closer to achieving true artificial intelligence anytime in the near future (it has only been 10 years away for the last 50 years). If I believe all of this, why strive to understand it better? Well, I believe that there is a place for some intelligence in machines, such as the Computer in Star Trek. Ideally, I would like to see something like Fuzzy Literate Programming — a way to specify what we want a computer to do in more flexible terms (read: more English-like) with the caveat that we won’t be specifying exactly what the computer must do; some sort of stepwise refinement must take place. I will probably write more about that concept as it continues to gel further down the road, but that idea is the main reason why I have an interest in AI.
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