On a related note, I've made wonderful progress in multiprocessing with Python, which (as you might imagine) takes a lot of futzing with things to get around the GIL. I hear rumors that Python 3 addresses some of this, we will see...
I believe that a lot of this anti-scientific thinking [not just ignoring science, but actively abandoning it] could be corrected if people accepted that theories may not be complete or perfect, but they are sound, and that this is okay. ...that we don't pretend to know everything about anything. ...that we create models about the world around us and update and improve them through testing and observation. ...that this doesn't dispute the entirety of our scientific knowledge, but just some details that were incorrect or inaccurate.
I've found that it's very difficult to get people [students, or in general] to accept that failure is not specifically negative - that we can/should/ARE SUPPOSED TO do this, and that this is how we learn and improve. I've also found that once they have accepted this, they become far more self-sufficient in learning.
"If we substitute 'more drivers' with 'more autonomous vehicles' and 'lower prices' with 'way lower prices,' it appears that the 'market' breaks. You could argue that an aggressive company could accomplish the same task now by simply paying drivers a flat hourly fee, even if there's no demand -- but it doesn't make any sense to do that because drivers are intrinsically temporary."
- Trinity UniversityPhysics, 1992 - 1996
- Trinity UniversityComputer Science, 1992 - 1996
- University of Colorado at BoulderAstrophysics and Planetary Science, 1996 - 2001
- University of Colorado at BoulderComputer Science, 1998 - 2000
- Trinity UniversityProfessor, 2001 - present
Department of Computer Science, 1 Trinity Place, San Antonio, TX 78212
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