Why is this guy hard to replace? There are tons of college stoners who have the skills to blow you any glass you want. Visit your local head shop if you doubt this. Why not get one of those?
He's saying that if you looked at the whole history of the US and divided that into 10 equal parts, then there would be a 10% chance of any random observation falling into the last part. Hence, all else equal, we have a 10% chance that we are looking at the US in the last 10% of it's history.
I can't really say what I imagine the alternative to be (if I could, I'd write it up), but I do know that if it had an inherent complexity in it's mathematical structure, I would image it to be more resistant to attack by a good mathematician than otherwise. At present we cannot prove that any of these algorithms is actually NP complete and the best device in existence to prove the conventional wisdom wrong sits between two ears. I think any algorithm designed to make the human brain less effective at analyzing it necessarily adds security, although I wholeheartedly cede the point that it also makes the flaws in said algorithm harder to find, so there is obviously a trade-off inherent to this approach. I also agree that any analysis will ultimately take a mathematical flavor (it is an algorithm of course, math is essentially the only trick humans have come up with here), but that isn't to say we can't craft one which makes that analysis fiendishly difficult. Thanks for the XSL link, I'm not a cryptographer, so wasn't aware of that.
I was mainly curious if any asymmetric algorithms exist which are not easily analyzed by algebraists, et al. According to the comment by tveita, this does not appear likely, and I am sorry to hear it. I don't discount what you say about mathematical algorithms being easier to analyze, so flaws are shallower. However, I have seen smart people do quite amazing things with mathematics in my life. People who spend years studying algebra or number theory learn so many patterns that the good ones can pull unbelievably clever arguments seemingly out of pure intuition. That is somewhat disconcerting to me because something like RSA or ECC is precisely the sort of problem those people can apply that intuition and pattern recognition towards. I obviously don't know of an asymmetric algorithm which is analogous, but something like AES is a nightmare to analyze algebraicly (it really does have that "jumble of shit" look to it when written out as an operator). That seems to me to offer some small resistance to the math genius with the spooky intuition. My main point was how dangerous a smart person can be with a problem that his/her brain is geared for, so I was curious if any algorithms existed which are not easy for a mathematician to attack.
As a mathematician (though not a cryptographer), I have a great deal of difficulty trusting cryptographic protocols which have a mathematical basis. Whether they are based on factoring, elliptic curves, or any other mathematical concept, they always "smelled" sketchy to me for the very simple reason that they are easy to formulate in terms of mathematical ideas, hence naturally lend themselves to the thought process of an algebraist or a number theorist. In short, these problems look like precisely the sort of questions a mathematical genius would find tractable. Without any solid proof that they are actually computationally hard to break, it seems like they are inherently dangerous to rely upon because they look like fair game to the next Ramanujan.
I'll also go out on a limb here and also say that I think the technology community has a bias towards thinking something like "math == hard" is true, so gives added weight towards using these same protocols. I know many people here have deep knowledge of both cryptography and software development, so I'd be very interested to hear other people's thoughts on these issues. Can anyone speak about options to math-based public key algorithms, or ways to inject some skepticism into the tech community about these algorithms, so perhaps alternatives can start being implemented? A public key algorithm which doesn't lend itself easily to algebraic analysis would feel much safer to me.
I agree on the pretty female observation. Just about every tech recruiter that's contacted me recently looks like someone I'd want to date. My father is a doctor in the US and the drug reps he deals with are also from this mold, so I guess that says something about what really works in male-centered professions.
The average defendant in the US is poor or indigent, often lacks much of a formal education, and is usually at the mercy of whatever overworked public defender they were assigned. Go ask any lawyer you know about how much weight their demands carry or how realistic a chance they have of getting evidence that has the patina of scientific certainty thrown out. I bet you discover they have about as much hope of that as a gnat trying to stop a locomotive.
I can't speak for CS, but I got a PhD in applied math at a respectable school in Virginia and about 90% of our grad students were not US citizens. To my knowledge, every one of them left on completion of their degrees and I can't remember a single one who actually expressed an interest in staying. I think people who see STEM grad students as some sort of huddled masses yearning for US residency are pretty out of touch with reality. This isn't 1960 anymore.
PhD in applied and computational mathematics (Old Dominion University, Norfolk, VA, USA) with published research in statistics, numerical analysis, and functional analysis. Strong interest in software development/engineering. Loves algorithms and programming challenges. Willing to learn anything. Happy to do statistics/data analysis as well. Comfortable with Agile/Scrum development methodology. Comfortable working remote, individually, or in a team.
I'm searching for work within the tech sector, preferably within Europe and Asia. I'm open to a wide variety of technical jobs and really want to have serious programming as part of my daily responsibilities. Get in contact if you are looking for someone with strong analytical problem solving skills and the willingness to put in whatever effort is needed to get the job done.
PhD in applied and computational mathematics (Old Dominion University, Norfolk, VA, USA) with published research in statistics, numerical analysis, and functional analysis. Strong interest in software development/engineering. Loves algorithms and programming challenges. Willing to learn anything. Happy to do statistics/data analysis as well. Comfortable with Agile/Scrum development methodology. Comfortable working remote, individually, or in a team.
I'm searching for work within the tech sector, preferably within Europe and Asia. I'm open to a wide variety of technical jobs and really want to have serious programming as part of my daily responsibilities. Get in contact if you are looking for someone with strong analytical problem solving skills and the willingness to put in whatever effort is needed to get the job done.
I agree wholeheartedly on the public drinking aspect. I lived in Virginia for 30 years and if you are walking around on the street with a beer, you're essentially asking to spend 4 hours in the "drunk tank" for public intoxication. This will be followed by offering some welfare ($) to the local legal profession to get the charge dismissed or pled down so you won't have a criminal conviction for your future employers to ask you about. There are similar laws in many other states and it definitely puts the kibosh on any potential block party you may wish to have. Since moving to Europe I find it pretty awesome to be able to enjoy a beer while I stroll and not worry about being run in so I can fund some lawyer's BMW lease.
One thing we learned from the Snowden revelations is that the NSA routinely uses convoluted legal justifications to do it's dirt. I'd be very skeptical that any slowdown/stoppage has actually occurred because it's likely they are simply continuing to operate under some other statute their lawyers have twisted around.
PhD in applied and computational mathematics with published research in statistics and numerical analysis. Strong interest in software development/engineering. Loves algorithms and programming challenges. Willing to learn anything. Happy to do statistics/data analysis as well. Comfortable with Agile/Scrum development methodology.