960 karma · joined January 17, 2012
With all due respect to pg, one data point against the idea that it's just the standards being too lax is that this article was posted on Hacker News in the first place. The Hacker News guidelines state that most stories about politics are off-topic unless they are evidence of some interesting new phenomenon. I've never read tech news sites where the H1-B debate wasn't going on (I've been reading since 2001 or so), and based on the mountains of H1-B rhetoric I've read online, the arguments raised in the article are not new.
The Koch brothers spent $31 million in 2012 to lobby for their coal power interests [1], which is linked to higher rates of lung cancer for miners, people who live near mines [2], and people who live near coal power plants [3]. I consider their cancer research donations restitution.
[1]: http://www.theguardian.com/world/2012/nov/07/oil-lobby-coal-...
More importantly, that difference is actually a big reflection of the underlying philosophy between the two terms. Free software is about maintaining the Four Freedoms (making tivoization a damaging loophole in the GPL), while open source is about arguing that the bazaar model is superior technically in order to sell it to business (and therefore tivoization is actually a plus to them). I believe this difference in intent should be noteworthy to the IRS in terms of evaluating whether a company is creating a nonprofit for tax-free software development as a form of corporate welfare.
The reason I ask is that the term "open source" was designed to be more palatable to businesses. In Revolution OS, Eric S. Raymond said in regard to saying open source over free software: "If you walk in to an executive's office and say 'Free Software', OK, If you're lucky, the response you'll get is something like, 'hmm, hmm, Free Software, must be cheap, shoddy, worthless.' If you're not lucky, it has associations with the Free Software Foundation's wholesale attack on intellectual property rights, which regardless of what you think about the ethics of that, it's lousy marketing, it's not something that businesses want to hear" [2].
I don't know how savvy the IRS was about the nuances between open source and free software (probably not very), but if they were, they might be making a somewhat-reasonable distinction that "open source" was designed specifically to please the business sector rather than free software's focus on ethics and freedom.
[1]: http://democrats.waysandmeans.house.gov/press-release/new-ir... [2]: http://www.cswap.com/2001/Revolution_OS/cap/en/25fps/a/00_54
[1]: http://quotes.liberty-tree.ca/quote_blog/Benjamin.Franklin.Q...
After an entire webpage was created to ridicule the Debian developers for how stupid they were when they changed something in OpenSSL's code in their distro's version (complete with references to Dilbert strips about faulty random number generators), I just assumed that I shouldn't even bother trying to look at OpenSSL's code (and especially not try to send patches or ask questions on their mailing list) unless I was willing to make a lifestyle out of it, lest I get ridiculed in the same way (but probably not at Debian's magnitude). I wasn't willing to make a lifestyle out of it.
As Steve Yegge says in "Done and Gets Things Smart," Cutler and Carmack are the types of engineers that companies file lawsuits over when they are hired away. This is because they generate a lot of extremely visible value -- most programmers are not perceived by legal departments to be worth suing over like that.
You'll find out real quick if you screwed up your Faraday cage design, though.
If you still believe your startup idea is a slam-dunk after seeing how horrible things can get if there's any hiccup in the process, then you're ready to take an investor's time to give a proposal.
I learned about Kalman filters in a mobile robotics course that made explicit Gaussian assumptions early on for the primary topic (SqrtSAM), and they brought up Kalman filters in its own lecture as kind of a "this is how they used to do SLAM" lecture. Considering the large amount of overlap in the methods, such as the use of linear covariance projections, I guess I made the assumption that Kalman filters had the same Gaussian assumption.
Although the Kalman filter retains some aggregate data about past states in its iterated covariance estimate, it is still primarily a recurrence relation where the future state depends on the immediate present, much like a discretized low-pass filter. This is part of why I'm intrigued by the parent article's use of a Kalman filter for this application.
This, of course, raises the questions of "who insures the Bitcoin insurance company" and "how do the insurance companies protect their Bitcoin now that they are a target?"