Damage to tissue (of any sort) tends to provide a good environment for bacteria to grow. I am wondering whether this applies to burns of the tongue, but can’t seem to find any information on it. It could be useful to know as a preventative measure for things like strep throat.
Gravitational clustering in machine learning, a previous idea of mine, has been done before, but it seems that you can also cluster points based on the Lorentz transform spacetime undergoes in general relativity. I’m wondering whether a data clustering algorithm based on the stress-energy tensor (simulated at relativistic speeds, of course) would be feasible. My dissertation is on using tensors in data mining, so it could be a useful example.
The only way you can avoid criticism of your ideas is to not have any… and at that point, you may as well be dead.
Everything we can directly perceive with our sight is contained in a band of light about 400nm across. This band of light happens to coincide with the type of light achieving penetration through earth’s atmosphere, which, of course, is not a coincidence at all. Our sense of sight grew up around this band of light and it would be foolish to expect extraterrestrial sources of life, should they exist, to see the same band. This throws another wrench into sci-fi cliches 🙂
The same goes for any sense that depends on properties specific to Earth or the Sun. For that matter, they probably couldn’t breathe our air, either.
There’s a video of cities at night up on Youtube. As beautiful as they say the cities are, one thing that struck me is the similarity in shape of some of the cities to tumors. This surprised me, since cities grow according to planned rules and tumors do not. Perhaps the conditions required for growth dictate a certain shape? Certainly the individual structures have analogues – blood vessels and roads, for example, both carry vital nutrients for their respective growths.
The interesting question is whether we can use any studies on the growth of cities to come up with tumor growth models as well, or even whether certain factors that plague cities could also be used to fight cancer.
This is such an important principle that I’m adding it to the philosophy I’m developing (yes, I know existing philosophies already incorporate it). There should be no conflict with the interests of the individual and the interests of society, because what benefits individuals ultimately benefits the whole society.
Leadership is coming up with grand ideas and motivating people to follow them. Teaching is motivating students to learn others’ grand ideas. They’re not that different, so good leaders probably make good teachers.
I’m starting to think over the policy of an ideal university in more detail while I wait for the foundation’s incorporation to process, and one of the areas I think is most important is admissions – the students are ultimately what make or break the university, after all.
To do this, I’ve been reading some recent articles about college admissions in competitive and noncompetitive schools, particularly in the context of the “Echo boom” that the current college-bound generation represents, and what I have seen is deplorable. To be sure, it’s something I’ve seen my entire life and always thought a bit… wrong… but I could never put my finger on why.
When I was in high school, I took 3 AP classes and considered this quite a bit. It was rather unusual to take any in my school, and certainly unusual to take more than one. Yet now it’s common for students to take 5 or more. What happened? Certainly they did not get any smarter in the six years since I graduated high school (quite the contrary – they seem less prepared now than they were in my day). GPAs keep increasing too, even though SATs (the most objective measure of the whole process, I would say) are fairly stationary. Many students were also taking extracurriculars and generally approaching an ideal.
This would be a great thing, except for the fact that the ideal belongs to the colleges; the students don’t share it. In fact, I’m willing to bet these students don’t have any of their own ideals yet.
And then I figured out what seemed wrong to me: these students do everything in their power to make themselves appear intelligent to schools, but they almost universally appear to lack the signs of giftedness that I had come to recognize so acutely: overexcitability, inquisitiveness, passion, advanced personal development, a degree of maladjustment, the beginnings of an ethical hierarchy, asynchronicity, and, most importantly, self-motivation. I’ve always seen these things go hand-in-hand with giftedness, but they were absent from the students.
Even more telling is the lack of a central theme to the credentials; an organization that tells me some sort of personal drive for improvement is taking place. I’ve come to see this as a prerequisite for leadership. Even my own diverse interests are tied together by the theme of my belief that taking on many things at once enhances knowledge and results in a more complete person.
Finally, evidence of self-reflection, which would at least indicate that there is potential for development, is absent. For all I’ve seen, these students may remain stagnant well beyond their college years.
So neither signs of actual leadership or giftedness nor signs of their potential are present. Lacking the self-motivation that spurs leadership, it is more likely that these students are motivated solely by external factors: perhaps the admissions process itself, or perhaps their families are spurring them on. These are the students our society has chosen to exemplify.
Some students are even going to what I would consider moral extremes: having others, such as counselors, write their essays for them (yes, I think this is morally despicable and I am proud to say that every word of every admissions essay I wrote was my own), suing other students and/or schools for valedictorian status, cheating on tests, bribing admissions committees, lying about their credentials, and so forth.
These are our society’s ideal students. What can I say? We live in a superficial society.
So now comes the fun part when you plan something that’s going to disrupt the status quo: we’re going to do things differently, so how do we fix this?
First, I’m hoping admissions can be very lax, because I believe far more harm is done by rejecting a good student than accepting a bad one. The bad student just drops out or transfers after a few semesters anyway, but the good student may never reach his potential if he isn’t accepted to the right school for his needs (the same thing applies for peer review in science, by the way). Already I’m clashing with the dominant model in admissions; that didn’t take long.
However, while the process should be lax overall, the ethical standards should be strict. The reason is simple: I don’t want liars and crooks to reach their potential. Ever. Why? Because they’d misuse the ability! Trained, a moral person with mediocre talent has a slighty positive to neutral impact on society, while an immoral person with extreme talent has an extraordinarily negative impact on society.
The review process for admissions should be iterative, with comments given midway through the process, because “we don’t like something but we won’t tell you what it is” isn’t a good model for anything.
The process should screen for qualities such as self-motivation, vision, true intelligence (might be hard to assess), leadership, and perhaps agreement with the nature of the university (for example, if my school is going to train polymaths, we’d want people who also want to learn a bunch of different things). Ideally, the goal is to find people who can set their own goals and work towards them. Lack of skill is ok, as that can usually be remedied, but lack of motivation is not.
The essays should focus primarily on self-motivated transformative experiences and accomplishments. “I did this after school, I did that after school” sorts of essays (and there are a lot of them) aren’t worth much. The reasons why students undertake such activities are more important, and should point towards a self-driven goal independent of the established expectations. The reasoning is pretty simple: polymaths go against today’s expectations by nature. Someone who must conform to those expectations because he or she has never gained the self-motivation required to go against them would not be able to follow such a path.
On the other hand, “I did this on my own” activities are much more valuable (although you still need the “why”). Independent thought of any sort is praiseworthy, and the ability to independently work towards your own ideas is one of the defining characteristics of a leader.
Finally, ensuring that the students are genuine and not just making a power grab is important. The requirement of justification for activities is a good step towards this, but we can add some others that will cover other areas. First, students can be admitted but should never be denied on the basis of GPA – not only are many gifted students underachievers (especially those in very unchallenging environments), but many people with high GPAs are not all that intelligent. GPA also changes, sometimes quite significantly, with environment (I personally went from having a 2.9 in high school to a 3.96 in college).
Students should also certify that their essays were their own work, on penalty of rejection if they are found to be lying. Other people reviewing is ok, of course, but no one else should be writing a student’s personal statement. If it doesn’t come from the student, it’s fake. It’s a tendency of admissions prep. services to make things up, as well, so the claims on the statement should be validated, right down to the extraordinarily inspirational advisor who doesn’t exist that many people seem to like putting on their personal statements. If we ask the “advisor” and he says he’s never heard of the student, or if he doesn’t exist at all, that’s enough grounds for automatic rejection.
That’s what I have so far. I’ll keep thinking about it more as it becomes closer to a reality.
You can always find someone who is great at an individual skill, and you can generally already leverage much of their work, potentially devaluing any further contributions in that area. When considering sets of complementary skills, however, the picture becomes much less clear, for far fewer people possess the required knowledge in all of these areas to successfully combine them. Thus, for a set of complementary skills, the real value comes from combining them.
This is “interdisciplinary fusion”. This is what I’m trying to impart to students with my idea for a new institution that trains polymaths. No one else does this because almost no one else can. They’re stuck in their narrow specialties, unable to leverage the knowledge at the intersection of the disciplines because they’re still trying to master them one at a time in isolation. I considered this approach once, several years ago. I came up with the conclusion that shaped my life since: you can master them faster in parallel. Much faster. Understanding breeds more understanding (if a sort of rigidity in thinking that should be consciously avoided). The more diverse the set of ideas you hold, the more you will be able to generate new ones.
Searching Google for “interdisciplinary fusion” shows that no one seems to quite get what I’m driving at – existing institutions propose curricula that span two or three disciplines and proclaim it “fusion”. First, any system that focuses only on a particular set of related disciplines is by nature incomplete, because a great deal of novelty is going to come from mixing wildly different disciplines, such as computer science and photography or mathematics and music. However, there is a more fundamental problem with existing systems: they fail to address the keystone holding the arch together! They attempt to impart interdisciplinarity without addressing the absolutely crucial intersection points that tie the knowledge together, instead teaching a bunch of unrelated courses that most students never dig deep enough to connect.
This is bad. Lacking that connection makes the whole system nearly worthless. And that is why it is one of the most important points I am going to focus on.
I just waded through a bunch of papers on the STARR and Rachev risk ratios. These seem to have vastly overcomplicated what you actually need to do, which is unfortunately typical of many mathematical papers (it’s a consequence of the logicians outnumbering the intuitives). I think I finally figured out what they were trying to say, and it turned out to be simple. I might still be wrong about this (after all, it was only an hour or so of deciphering), but here’s how I think the concepts can be summed up easily and intuitively for someone who understands a bit of statistics:
First, get a distribution of excess return by subtracting your returns from the value of a risk-free investment.
Value at risk: Find the qth percentile/quantile of the return; that is, q% of the time, you’ll make less than the value you find. If you assume a normal distribution, you’re just finding the z-score from the p-value q (hint: the Excel NormInv function will do this for you, or you can grab a normal table if you’re old-fashioned). If q = 0.05, that’s 1.96 standard deviations below the mean using a two-tailed test (one-tailed, it’s a bit less).
Conditional value at risk/Expected shortfall/Expected tail loss: Average of everything in the distribution where returns fall below the value at risk. Since the value at risk represents bad things with an unlikely probability (q%) of occurrence, this is the average of all of the really bad, really unlikely things that could happen to your portfolio. Oh, and it’s a loss, so if you’re dealing with a distribution of returns, you’ll want to negate the result.
STARR ratio: Excess returns over expected tail loss. It seems to measure how much you typically make vs. how much you can possibly lose. Average over worst case.
Rachev ratio: Tail loss of losses (just negate the returns distribution!) over tail loss of returns. Loss of losses (let’s call it “gain”) is a good thing, so the numerator represents what you can gain in the best q% of cases, while the denominator represents how much you can lose in the worst q%. Essentially, you’re judging the best possible case against the worst.
When you get down to it, the intuition behind the concepts is simple. It’s just dressed up funny. Unless I’m totally wrong about this 🙂
You can probably use these sorts of ratios in other fields as well, particularly when the terms “best case”, “average case”, and “worst case” have meaning, such as in the analysis of algorithms.