Many of my friends didn't see anything unfair about heavy taxation and redistribution of wealth while they were students (and therefore paying no tax and probably claiming some sort of state funding toward their tuition expenses). In most cases, their views changed rather abruptly when they got their first real pay slip and looked at the deductions column.
That may be, but then they are being manipulated. Anybody outside the top 5% of income isn't having "wealth" redistributed because they don't have wealth; they are simply paying for what they are using. Your federal taxes primarily go to the US military, interest, roads, and entitlements. If you want to lower them, elect people who reduce spending on those (hint: most politicians increase discretionary spending and thereby your tax burden, with Republicans being even worse than Democrats).
so it's not surprising that their views on ethical issues like copyright infringement come from a one-sided perspective.
You are implying that it's accepted that infringing copyrights is unethical; that is false. Copyrights are not property rights or natural rights; they were created relatively recently as a pragmatic step to encourage publication. The traditional view of ethics is that creations should be properly attributed, nothing more. The notion that a law can restrict the use of ideas or words remains bizarre and unnatural, and rightly so.
It is, of course, regrettable how quickly certain people who have come through the education system and started work in knowledge industries forget their first perspective in their haste to advocate their second.
I don't know where you get that from. Most of the creative people I know in the computer industry consider the current copyright and patent system to be both economically bad and ethically unjustifiable, a view that only gets reinforced the longer they work in "knowledge industries" and see how the current system is not working and doing a great deal of harm.
I wouldn't fault Wolfram for making this mistake; people do make mistakes. Wolfram's problem is with science, not bookkeeping: not properly crediting other people, trying to claim results and breakthroughs without having done the hard work to prove them, etc.
Wolfram was not the first to formulate the ideas in "A New Kind of Science", and if they should turn out to become the foundation of physics over this century, the key ideas needed for making that happen will not have come from his book. That's the real problem with Wolfram.
It's generally not a good idea to rely just on Nelder-Mead; there are many problems for which it simply doesn't yield good results.
What really makes me slow to move is that my university just negotiated a site license, so MATLAB is free, increasing my dependance on the program.
It may seem "free" now, but the more you get addicted to it, the more Mathworks can charge you later, and they will. It's least expensive to kick the habit early on.
The standard motion picture format is MJPEG2000. It's not a very efficient format, but it's well defined and going to be around for a long time: there's both a lot of hardware and software that relies on it, and it scales up to high resolutions.
The consumer format wars between Microsoft, Apple, Sony, and other companies have no influence on this.
Like Windows, Matlab has become too popular for everyone to just drop and move on to some other platform
That implies that Matlab has a near universal hold on numerical computing; that is simply false. Both Python and R are widely used in many disciplines. Furthermore, Python has so much more useful functionality than Matlab that there can be a strong motivation for many people to switch when they learn about it.
1. I know how to code in Matlab. I have spent the last 13 years writing matlab code, and it works well. It is especially good at writing vectorized code without having to think about it too much.
That shouldn't be a big obstacle; SciPy supports all the core Matlab functions using Matlab's function names. Your expertise will carry right over.
2. I have a lot of working, tested code that I don't want to have to re-write. Much of it is special-purpose stuff, and I don't want to have to re-write it and then test it to make sure that it gives the correct answers.
That's sort of a valid argument; however, converting code from Matlab to SciPy isn't hard, and it often improves the code. Also, there are ways of integrating Octave and Python.
3. Sometimes languages that are good for one thing are not good for another.
Sure. But the Python language is actually very good for scientific computation, better than Matlab in my experience.
Ironically, the lack of pointers, something that computer scientists think is terrible,
Computer scientists generally don't like pointers either. The only people who like them are C and C++ hackers, only a few of which happen to be computer scientists.
You want to get rid of him, but, since being CEO for this sort of company is an intrinsically high-paying job, he obviously resists getting the boot. Assuming you don't have anything strong enough to outright fire the CEO,
You may have a hard time firing him quickly, but you can easily put him on paid leave and keep him from screwing up any further. The amount of money at issue then is just his salary, not the corporate earnings or losses.
Octave is a great effort, and it is very useful for being able to be able to run Matlab code freely. However, most of the effort in open source numerical computing is happening with NumPy and SciPy (www.scipy.org). For most applications, SciPy is already far superior to even the commercial version of Matlab, and SciPy is the de-facto standard in several scientific communities. There are a few areas where Matlab still has toolboxes that have no good equivalent for SciPy yet, but that's going to get fixed.
So, if you're looking for an open source Matlab alternative, use SciPy for new development and stick to Octave only for occasional backwards compatibility and testing during porting.
Slashdot Mirror
Many of my friends didn't see anything unfair about heavy taxation and redistribution of wealth while they were students (and therefore paying no tax and probably claiming some sort of state funding toward their tuition expenses). In most cases, their views changed rather abruptly when they got their first real pay slip and looked at the deductions column.
That may be, but then they are being manipulated. Anybody outside the top 5% of income isn't having "wealth" redistributed because they don't have wealth; they are simply paying for what they are using. Your federal taxes primarily go to the US military, interest, roads, and entitlements. If you want to lower them, elect people who reduce spending on those (hint: most politicians increase discretionary spending and thereby your tax burden, with Republicans being even worse than Democrats).
so it's not surprising that their views on ethical issues like copyright infringement come from a one-sided perspective.
You are implying that it's accepted that infringing copyrights is unethical; that is false. Copyrights are not property rights or natural rights; they were created relatively recently as a pragmatic step to encourage publication. The traditional view of ethics is that creations should be properly attributed, nothing more. The notion that a law can restrict the use of ideas or words remains bizarre and unnatural, and rightly so.
It is, of course, regrettable how quickly certain people who have come through the education system and started work in knowledge industries forget their first perspective in their haste to advocate their second.
I don't know where you get that from. Most of the creative people I know in the computer industry consider the current copyright and patent system to be both economically bad and ethically unjustifiable, a view that only gets reinforced the longer they work in "knowledge industries" and see how the current system is not working and doing a great deal of harm.
Unlike other Google products, Google Reader doesn't work over SSL, so it's not secure to begin with.
Google Reader has a nice user interface, but until that gets fixed, I'm not using it at all.
... more penetration testing
I wouldn't fault Wolfram for making this mistake; people do make mistakes. Wolfram's problem is with science, not bookkeeping: not properly crediting other people, trying to claim results and breakthroughs without having done the hard work to prove them, etc. Wolfram was not the first to formulate the ideas in "A New Kind of Science", and if they should turn out to become the foundation of physics over this century, the key ideas needed for making that happen will not have come from his book. That's the real problem with Wolfram.
My biggest thing that I depend on is the fminsearch function.
Fminsearch is just the Nelder-Mead simplex algorithm. It, and many other optimization methods, can be found in this SciPy package:
http://www.scipy.org/doc/api_docs/SciPy.optimize.html
It's generally not a good idea to rely just on Nelder-Mead; there are many problems for which it simply doesn't yield good results.
What really makes me slow to move is that my university just negotiated a site license, so MATLAB is free, increasing my dependance on the program.
It may seem "free" now, but the more you get addicted to it, the more Mathworks can charge you later, and they will. It's least expensive to kick the habit early on.
The standard motion picture format is MJPEG2000. It's not a very efficient format, but it's well defined and going to be around for a long time: there's both a lot of hardware and software that relies on it, and it scales up to high resolutions.
The consumer format wars between Microsoft, Apple, Sony, and other companies have no influence on this.
Like Windows, Matlab has become too popular for everyone to just drop and move on to some other platform
That implies that Matlab has a near universal hold on numerical computing; that is simply false. Both Python and R are widely used in many disciplines. Furthermore, Python has so much more useful functionality than Matlab that there can be a strong motivation for many people to switch when they learn about it.
1. I know how to code in Matlab. I have spent the last 13 years writing matlab code, and it works well. It is especially good at writing vectorized code without having to think about it too much.
That shouldn't be a big obstacle; SciPy supports all the core Matlab functions using Matlab's function names. Your expertise will carry right over.
2. I have a lot of working, tested code that I don't want to have to re-write. Much of it is special-purpose stuff, and I don't want to have to re-write it and then test it to make sure that it gives the correct answers.
That's sort of a valid argument; however, converting code from Matlab to SciPy isn't hard, and it often improves the code. Also, there are ways of integrating Octave and Python.
3. Sometimes languages that are good for one thing are not good for another.
Sure. But the Python language is actually very good for scientific computation, better than Matlab in my experience.
Ironically, the lack of pointers, something that computer scientists think is terrible,
Computer scientists generally don't like pointers either. The only people who like them are C and C++ hackers, only a few of which happen to be computer scientists.
You want to get rid of him, but, since being CEO for this sort of company is an intrinsically high-paying job, he obviously resists getting the boot. Assuming you don't have anything strong enough to outright fire the CEO, You may have a hard time firing him quickly, but you can easily put him on paid leave and keep him from screwing up any further. The amount of money at issue then is just his salary, not the corporate earnings or losses.
Octave is a great effort, and it is very useful for being able to be able to run Matlab code freely. However, most of the effort in open source numerical computing is happening with NumPy and SciPy (www.scipy.org). For most applications, SciPy is already far superior to even the commercial version of Matlab, and SciPy is the de-facto standard in several scientific communities. There are a few areas where Matlab still has toolboxes that have no good equivalent for SciPy yet, but that's going to get fixed.
So, if you're looking for an open source Matlab alternative, use SciPy for new development and stick to Octave only for occasional backwards compatibility and testing during porting.