Achieving Goals in Computer Science: Finding Motivation

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SUMMARY

This discussion centers on finding motivation in the field of Computer Science, highlighting key areas of interest such as remote rendering systems, virtual environments, and computational neuroscience. Participants emphasize the importance of formal language theory, parallel programming structures, and kernel methods, particularly in the context of scientific computing and real-time systems. The conversation also touches on the limitations of current processing power and the potential future impact of Exaflop GPUs on these fields. Overall, the discussion encourages exploration of diverse topics to enhance motivation and engagement in Computer Science.

PREREQUISITES
  • Understanding of formal language theory
  • Familiarity with parallel programming structures, including data parallelism and threading
  • Knowledge of kernel methods, specifically support vector machines
  • Basic concepts in scientific computing and graph algorithms
NEXT STEPS
  • Research advancements in remote rendering technologies and OnLive-type systems
  • Explore virtual environment development tools and frameworks
  • Study computational neuroscience applications in AI and machine learning
  • Learn about compiler construction techniques and their relevance to formal verification
USEFUL FOR

This discussion is beneficial for Computer Science students, researchers in AI and computational fields, and professionals seeking to enhance their motivation and focus on specific areas of interest within the discipline.

CylonMath
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What is your purpose in field of Computer Science ? Do you have any idealistic aims ? As we know it is the one of the leading fields of world in next years, what kind of targets can be constructed to increase your motivation level to work hard ?
 
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There are three things in particular that have captivated my interests.

1. Remote rendering (OnLive-type systems)
2. Virtual environments
3. Computational neuroscience

I wanted to venture into particle systems and real-time natural lighting right off the bat, but I realize the constraints of processing power even today are too limited for my imagination. However there are plenty of interesting things to do for the time being prior to Exaflop GPUs.
 
There are a few areas that captivate me in cs
1) formal language theory
2)research in parallel programming structures (data parallelism and threading, distributed)
3)kernel methods (support vector machines and parallel models of such)
4) compiler construction

also of interest is parallel implementations of financial models for things like option pricing and pricing derivatives, etc, but this is hardly cs

These are my main interests and the main areas i have been involved in. My favorite is formal language theory because i am originally from a math background.
 
Some of my areas of interest...
(1) Scientific computing
(2) Graph algorithms
(3) Real-time and embedded systems
(4) Computational physics
 
1. artificial intelligence (statistics, information theory, neural networks, etc)
2. computer languages, type theory, formal verification of computer programs
3. organizing and representing information for human consumption (e.g. diagrams) (perhaps not really a CS topic)
4. Misc.
 

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