Monday, January 31, 2005

Hmm..

Well, I guess this makes me a real geek now. :-) Anyways, I moved my blog from my account at the university computers to here. I wanted more freedom to write things that really reflected my current state of mind, so, I finally did it -- I'm an official blogger. I've been fighting the urge for a couple years now, but it was inevitable. I only reposted stuff that others have found interesting.


Grand Challenges in Comp. Sci.

Jan. 26, 2005 -- Here's a real interesting article that appeared in yesterday's edition of InfoWorld. (You can get the actual conference report here.)Essentially, some computer scientists from Britain outline 7 "grand challenges" in the field of IT that will be faced over the next one to two decades. This is VERY interesting, and if you are wondering what areas of research in Computer Science to get into over the next 3-5 years, you should seriously read this document.

Summarized, they are as follows:

  1. In Vivo-in Silico (iViS): the virtual worm, weed and bug -- They outline the necessity of developing computer systems that behave and simulate living organisms. Their argument is that this would allow us to better understand and comprehend living organisms in ways we have yet to observe.
  2. Science for global ubiquitous computing -- (Read #4. This should have been included in that section.) Realizing that computers are becoming pervasive and ubiquitous is continuing to open numerous areas of research.
  3. Memories for life -- The claim is that the number of people digitizing their life is growing exponentially. (e.g. Photos, video, important documents, etc..) This is creating information overload. New areas of research are opening up to allow this enormous amount of data to be easily managed, that will tap into areas such as security, privacy, databases, information retrieval, AI, machine learning, HCI, etc..
  4. Development of a global, scalable ubiquitous computing infrastructure -- Do any type of current research into ubicomp, and you'll clearly see the need for commonality in this field. The number of computers all around us is exploding. The potential areas of research is again, security, privacy, context awareness, self-configuration, seamless communication, numerous human factors (this stuff must be invisible to us, otherwise we're not going to use it), etc.
  5. Better understanding of the brain and the mind -- This has more of a philosophical background of interest. We all should realize the most powerful computing machinery on the face of this earth is your brain! Some view the brain as being analogous to computing machinery and the mind as virtual software. Our brain does so much that we barely understand. Perhaps better understand of how our mind works can open opportunities in CSI.
  6. Dependable systems evolution -- To me, this should have been the number one focus of the conference. Without better methodologies that allow more dependable systems, while still saving on time and money, none of the above will be able to happen. Regardless, they outline the development of a verifying compiler that can prove the correctness of the
    program before being run.
  7. Journeys in non-classical computation -- It's time to go well beyond much of the traditional theory of computation as has been research and open doors to new paradigms. Classical computing, which most would agree is the Turing Machine model, is not an adequate model of reality for all notions of computing. Take quantum computing as an example...

Very cool.

Tuesday, January 25, 2005

Grad School -- The Board Game!

Check out the comic this out...

http://www.phdcomics.com/comics/archive.php?comicid=515

I wasn't sure whether to laugh or not... as this is a little too much truth for my humorous side. In our department, we call the PhD qualifying exams (or quals) "analytical exams" (or analytics, or, as I like to say, "anals"). Don't ask me why they just don't call them quals. Anyways, the chances of passing all of your exams the first time are roughly 1/36, so that's pretty accurate. Let's see, what else? Hmmm... yes, I certainly take part in all opportunities for free food around the campus. I can understand what happens when a department loses funding. It sucks. I can relate to what happens when you generate bad data, or worse yet, you have good data, but you can't reproduce it, which is still bad data. (Been there.) Generally, choosing a research topic is not so different than drawing a card from the Chance deck. This is funny! If you're a PhD student, you must visit the site http://www.phdcomics.com. I assure you that you will be able to relate to most of these clips.