Design Perceptive

Finally!  My bachelor’s is out of the way and I . get on to the really cool stuff.  I am starting grad school in the Spring under Dr. Manfred Huber.  This is under the purview of the Computer Science and Engineering department’s new BS-to-PhD program.  The program goes something like this:

• 4 core courses (total of 12 hours)
  • Algorithms + 3 of OS, Compilers,Architecture and Data Modeling
• 9 hours of 6000-level subject area coursework
• 9 hours of Research-oriented coursework
• 18 hours Dissertation

I start with AI-II, Algorithms and a 6000-level research course.  I won’t have to purchase any books.  My friend, Kartik, will be giving me his Algorithms book and the AI book is the same from AI-I.  I still have that one.  This is a pretty exciting time for me.  Of course, my major area of study will be Artificial Intelligence, but that’s a very big field.  I’m using the research course to look about and see what I want to do.  I also hope to publish out of it.  I’m sure it won’t be anything spectacular, but if I can use my time in any of my classes as an angle to publish, then I’m going to try to do so.

My next major milestone will be to pick my committee.  This will be in the 3rd or 4th long semester.  So, I am shooting for Spring or Fall of 2011.  Diagnostics will occur in the 4th or 5th on completion of 30 graduate hours.  The comprehensive exam occurs two long semesters after diagnostics.  Then, research proposal one semester directly after that.  Finally, my defense is some time after that depending on how quickly I can do the research and write the dissertation.  They give a 99 credit-hour/14 long semesters limit before having to pay non-resident tuition.

I had better get on it.

I like the concept of a minimalism when it comes to the home. It appeals to the senses by simplicity. And, in my opinion, one characteristic of a minimalist home is that it requires minimal effort to run and maintain. In other words, it is very hands off. So, I’ve been working with intelligent control systems, adding them as I can. Recently, I installed a simple timer-based irrigation system for my garden and patio.

Now, I’ve started looking at controls for the HVAC. I want to be comfortable, but I don’t want to have to deal with the thermostat anymore. I also want to save money, but I don’t want the hassle of trying to figure out everyone’s schedules and programming the system for that. Now, these goals are somewhat contradictory. If I wanted to maximize my money savings, I simply turn off the AC. But, that costs me in terms of comfort. If I want to be comfortable I run the system, and I am going to incur operating expense. There’s a balance here somewhere.

So, after a little foray into a Research Experience for Undergrads, where I did some research into intelligent control systems, I’ve decided to start wiring up my house. I have a good thermostat that gives me the ability to control the HVAC via my computer. I can also read information about the temperature in the house.

I also need to keep track of who is home and who isn’t. To do this, I’ve enlisted the help of Google and my cell phone. Every so often, my phone tells Google where it is. I can pull this information straight off the web through a nifty URL Google provides. I currently have my home computer doing this every 10 minutes. I’m going to let it run tonight and all day tomorrow.

I propose to use this mechanism to train an artificial neural network designed to learn my occupancy patterns. This can be used to determine if I’m going to be home at any particular time, giving my HVAC something to work with to determine when it should operate.

I’m in the second, and final, semester of Senior Design in the Computer Science program at the University of Texas at Arlington.  One of the requirements of this curriculum is to sit a panel discussion.  Each member of the panel must give a 10 – 15 minute presentation and then be prepared to discuss and answer questions.  My panel sits about 4 weeks from now.  Naturally, but unlike some of my fellow students, I’m preparing now.  I mean, this type of thing is part of what I want to do for a career.

Anyways, the topic I’ve been assigned is “What are the social implications of artificial general intelligence?”  Yeah, I know I could fill an entire semester with this topic, but I only have an hour in which I must present and represent.  So, I’m trying to come up with a decent presentation that introduces the concept of AGI, discusses some of the popular conceptions of what happens when we do create AGI and what the social implications might be.

Going through this exercise is synthesizing some of my own thoughts.  Though they might not be novel, I’m writing them down here as a way to remember the path; a breadcrumb if you will.  It may be that I find support in the literature for these ideas, find that someone has already thought of these, etc.  That would be fine – I just need to get them out.

First, it seems to me that motivation is a key element in AGI.  Maslow’s Hierarchy of Needs might then play an interesting role as part of a motivational system for a generally intelligent agent.   I’ll be looking into this concept and discussing more of it here later.

One of the great things about being in academia is that I get to write really pretentious titles for things, just like this one.  Instead of simply saying that this first post is going to be about me, what I think, how I learn, who I am, and random wandering to other topics, I get to use really fancy words to obfuscate (there’s another fancy word!) the matter at hand; however, that’s going to be the first point I want to make today: the tendency for science (especially Computer Science, my chosen field) to obfuscate, why this occurs, why it shouldn’t occur, and ways to stop it.

The question of why is the hardest of the three, so let’s start with that.  It is my opinion that the “need” in CS (as I will refer to it from here on out because it’s really annoying to write “Computer Science” every time) for overly complex explanations, jargon and equations written largely in Greek comes from a seemingly subconscious need to “prove” CS as an academic discipline, despite all the wondrous advancements in life as we know it that would not be possible without CS.  Computer Science has only been around since the 50’s, which makes it still a relatively new discipline, and it seems that, from my experience, to be considered one of the preminient academic disciplines, youhave to talk and write like you read the dictionary as a kid.

Just look at medicine (one of the oldest disciplines, though for most of civilization doctors were absolute quacks) or it’s siblings biology and chemistry; they still use Latin as a primary language, and have an entire field dedicated to nomenclature.  Deep in the heart of every computer scientist there is the desire to beat the other sciences at their own game.  Plus, CS evolved from Mathematics (and many feel CS is an “applied math”) which, if you’ll recall, eschews words altogether and does business solely with characters from various alphabets, including Arabic and Greek.  This means that whenever a computer scientist has to represent a potentially complex or difficult idea formulated through their research, they have to represent it in a Greek-character-laden equation.  If they don’t, their idea is rejected by the CS community and their work will go unpublished, and to be unpublished in any scientific academia is the kiss of death.

In short, CS is the kid who, in an attempt to prove to all the older kids that he’s just as smart as they are, goes home to study a Word-A-Day calender.

So why does this matter?  Why shouldn’t CS obfuscate itself, cackling and pointing fingers at people who don’t “get it” while it high fives the other sciences in-between hands of Magic: The Gathering (okay, I’m taking this metaphor a bit far)? Because, metaphorically, that’s a very lonely life.  One will never get the fully rich cavalcade of experiences if one doesn’t open oneself to viewpoints that are outside what it deems “acceptable”.  I wonder if we in the CS community have already missed out on developments that could and should have occured had we not eliminated from contention people who had the chops to design or discover great things but couldn’t or wouldn’t bring themselves to the level of intellectual bullying that goes on in the academic sciences.  ”You don’t know how to solve complex quadratic equations, hur hur hur!”.  Luckily this is slowly beginning to right itself as more companies follow the Apple modus operandi of design and ease-of-use being as important as technical expertise (if not more so).

This, of course, is where an intrepid reader might be making the comment that what I’m describing is really a delination between a computer scientist and a computer engineer.  A scientist seeks to ask “how do things work?” or “why are things the way they are?”, whereas an engineer seeks “what can do I with this?” or “where can I apply this?”  And maybe they’re right.  It still doesn’t negate the idea that, even when one is taking the potentially more complexscientific questions (versus the more pragmatic and practicalengineering questions) one still should seek clarity in their writing and in their lecturing, lest we shut down brilliant minds before they have a chance to germinate.

There are ways to fix this, of course, but unforunately we in CS have already shot ourselves in the foot;  there actually exists a series of books with the intention of teaching topics that have been thought to be too “complex” for leyman, and to teach them with clarity and conciseness… and then they were called the “For Dummies” books.  You can imagine the aforementioned table of nerds snickering about having to explain their favorite subjects to “the dummies”.  Why do you have to be a “dummy” to want things explained in a straightforward, understandable manner?

So, how to conclude all of this… I know!  To borrow common slang from Internet message boards, I can provide “cliffnotes” in case this was “tl;dr” (too long, didn’t read).

• Computer science makes things overly complicated
• They do this for many reasons
  • To try and prove that they are just as “tough” as the older sciences
  • Because they originated within mathematics
  • Because it’s their own way of being a bully
• This has potentially eliminated talented designers from being computer scientists
• The “For Dummies” books only further this misdirection

With that, I’ll sign off for now.  Till next time, this was John.

P.S. – The irony does not escape me that, throughout an essay on the pitfalls of being overly complicated, I used many esoteric terms and fancy words (”portmanteau”?  Come on!).

    

 

 

 

 

zeno-cute-at-nextfest

I don’t remember the origins of my desire to become a college professor.  Yet I know that the thought first crossed my mind when I was a sophomore in high school around the age of sixteen.  I speculate now that there was a congruence of influences that resulted in a life vector oriented towards academia.  I suppose these influences would include a deep respect for my teachers versed in the magical aspects of mathematics, a profound admiration for certain people in my life who had attained their graduate degrees and an exposure to and affinity for science fiction which often drove my dreams and inspired me toward science and technology.  By that time I had gravitated towards computers.  The Apple IIe was new in our school’s administration office and a family friend was teaching me RPG on an IBM running System/360.  I was reading about Marvin Minsky, about Artificial Life and about using genetic algorithms to solve problems.  I had experienced the proliferation of robots in the popular media and I was hooked.  I knew that artificial intelligence and robotics were the two topics that I wanted to study.  So, if my admiration and respect for those in academia can be called the strength of my vector at that point in my life, then AI/Robotics was certainly my orientation.  Unfortunately, other life choices were made in my early adulthood and my studies in that area became more of a hobby than anything else.

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