Yucky. Ppl spend 10K on Zynga games? Who are these fools?
"Big Brother Zynga
I worked at Zynga for 8 months, I can tell you all about the Good Stuff (yes, there is good stuff going on in there!), and the nasty-douchey stuff (yes, there is extremely CREEPY stuff going on in there!) [..].
Spying on players. Getting intimate gaming data, their habits, their networks, and how to effectively monetize given X [..].
Another issue was skewing gameplay for the sake of profit, example; I actually resorted to BAD MATH, to make the case for making a feature more fun. At the end of one sprint, a QA dude was complaining about the drop rate of a specific item being absurdly insane, and therefore UnFun. I looked at the code, and tweaked some values, gave it back to QA guy, and fun was restored. Product Manager overrides this, goes for unfun, yet more profitable version [..].
Internal metrics researchers often give studio wide talks on what trends are going on. They've basically tracked down very popular players and also players who've spent an excess of 10k into the game [..].
We often tweak our features to match and maximize for a particular gaming habit. We do this for massive populations of players. Players are not aware of this. To me, that's a big brother like issue, someone is measuring and monitoring your behavior intimately, and you don't know how that data is going to be used."
Giordano Bruno (1548 – 1600), was a philosopher, mathematician and astronomer. His cosmological theories went beyond the Copernican model in proposing that the Sun was essentially a star, and moreover, that the universe contained an infinite number of inhabited worlds populated by other intelligent beings. He was burned at the stake by civil authorities in 1600 after the Roman Inquisition.Bruno was deeply influenced by the astronomical facts of the universe inherited from Arab astrology, Neoplatonism and Renaissance Hermeticism. He is said to have made a threatening gesture towards his judges and to have replied: "Maiori forsan cum timore sententiam in me fertis quam ego accipiam meaning "perhaps you pronounce this sentence against me with greater fear than I receive it."
Halftime in America
Kevin Hart
New find; Kevin Hart. I like the bit about his kids.
Know-How and Why
Science education needs to focus on the process, on mathematical modeling, on how to obtain results, instead of simply results themselves. There is some improvement in this regard, but the old approach and culture still persists. Even the greats of teaching were not immune to this problem; The Feynman Lectures on Physics is mostly about results rather than the process used to obtain those results. The real gold is in the process, the results can change. In Genius we read at a young age Feynman reached a point when he could model pretty much anything he wanted, he'd run around asking people for problems to model, and finally found one;
"No one had ever analyzed the behavior of light passing through a parade of mostly transparent films thinner than a single wavelength [..] A few days later Feynman returned with the solution: a formula summing an infinite series of reflections back and forth from the inner surfaces of the coatings. He showed how the combinations of refraction and reflection would affect the phase of the light, changing its color. Using Feynman’s theory and many hours on the Marchant calculator, Cutler also found a way to make the color filters his professors wanted. Developing a theory for reflection by multiple-layer thin films was not so different for Feynman from math team in the now distant past of Far Rockaway [his childhood home]. He could see, or feel, the intertwined infinities of the problem, the beam of light resonating back and forth between the pair of surfaces, and then the next pair, and so on, and he had a giant mental kit bag of formulas to try out."
Representing functions are sums of infinite series is a deeply theoretical subject whose research was inspired by physics, beautiful mathematics. Tranmission of such "mental kit of formulas [or equalities, inequalities, theories, representations, etc]" should be the goal of education, not simply dropping a finished product / formula F = ma in a kid's lap, and have him / her solve mechanical problems one after another.
Who Need Access? You Need Access!
Our governments spend millions on funding research. Scientists do the work, write up their results as papers, format the manuscripts, prepare figures, and send them to publishers. Other scientists handle editing for the publishers (unpaid). Yet other scientists review the manuscripts for the editor (also unpaid). The result of all this is a honed and polished research paper. But all too often the publisher demands the copyright, and locks the research behind a paywall. (Needless to say, they don’t pay the author, either.)
The result is that the taxpayers who funded the research don’t have access to it.
“So what?”, you might ask. “I don’t want to read research papers.” [..] The reality is that there are many groups that want and need access to the research that they and you funded. Public access to scientific research makes all our lives better: it makes us healthier, better governed and better educated; it lets us live in a cleaner environment, a more civilised society and a healthier economy.
My kinda car
That's a wood-burning stove in there!
Nice Action (Indian Movie)
https://youtu.be/7yBnl_krN_U
Crises Economics, Roubini
As securitization became increasingly commonplace in the 1990s and 2000s, mortgage brokers, mortgage appraisers, ordinary banks, investment banks, and even quasi-public institutions like Fannie Mae and Freddie Mac no longer subjected would-be borrowers to careful scrutiny. So-called liar loans became increasingly common, as borrowers fibbed about their income and failed to provide written confirmation of their salary. Most infamous of all were the “NINJA loans,” in which the borrower had No Income, No Job, (and no) Assets.
Here is a great book on Islam and science. I perused through it, and boom: found a passage that talks about how Greeks were busy with science but Byzantium Empire wasnt. Frankly I am quite tired of being right on this issue: Romans, Byzantium and Ottomans represent a dark chapter in human history whose ill-effects persist even today.
P ≠ NP?
In theoretical computer science a distinction is made between branch-and-bound problems, and stuff that is computed in linear time. Solutions for NP problems try all possibilities, but for every found potential solution, its correctness can be checked in linear time. Shortest route from Boston to New York? Try'em all! If you have the final solution will be blatantly obvious; is New York in the list? If yes, you are done. P problems are anything efficiently solveable. Almost all of the applied mathematics is in P.
I argue that fussing over P ≠ NP is pointless and waste of energy. Feynman once said [paraphrasing] "some problems are just harder to compute [numerically]". So he was like "so what?". NP problems are foreign to physicist because their math is designed to keep them in P. If they come across intractable computation, they will throw simulation, other numerical tricks at the problem, but this either a) never happens, or b) won't be pursued until it is absolutely necessary. Algebraic derivation continues for a long time, twists and turns, sometimes in order to avoid intractability, sometimes for other reasons; and when finally there is a formula, usually it is already in P.
Some argue that the data generated by the Internet, images, video, sound, result in problems that are inherently in NP. I disagree. PDE based methods are applied to image processing successfully, and noone knows how much in P we can remain and still succeed solving these problems, because we haven't tried them yet. To me, pattern equals tractable math and that equals P.
Surely being able to solve NP problems, using paralellism, quantum computers, multicore architecture is necessary, a different research track on its own, what I am saying is there is a wealth of mathematics, modeling that is essentially P material. Mathematics, applied or not, is mostly about exploiting properties of numbers so they give us computable solutions in linear time. I am using the word exploitation here, with good reason. Some tricks are akin to dressing up a monkey and making it dance. Monkey dont know it, but it is dancin, and doing something for its viewers, conciously or not. That takes genius, creativity, understanding the problem domain and a good amount of mad skillz.
A like-based system for artistic products (or even other things) can result in interesting side applications. Each creation in the registry can also carry a list of references, or sources that the creation used as its inspiration. Then, every "like" (or a portion of it) received by this creation can automatically be distributed people in the references list.
Corollary: In our general scheme, copying and stealing is encouraged, and no punishment of any kind is condoned. That said, potential disagreement in this scheme can (should) be around the issue of reference, that is being cited properly in a digital work, thus "missing out" on the likes received by that work. Therefore, it is conceivable one involving a legal mechanism of sorts in order to be included in a reference list. That is ok. But again, no punishment, and rabid stealing (copying) is encouraged and in fact the prime f...ing directive of this system.
Psychology & Computation Link
There are interesting parallels between algorithms / computation and Jungian psychology.
Si is introverted sensing, it looks at the current events and "remembers" similar events, objects, sayings from the past. Then, Si is basically a nearest-neighbour approach that is used in Machine Learning. It has no model, the model is the data itself.
Ti is the ultimate modeler. It tries to summarize data, tries to set clear boundaries between definitions so that categorizations and predictions are more accurate. Ti in ML is anything that uses a graphical, analytical, structure based model such as Bayesian Nets, ID3, or already cooked up formula with some missing parameters. Si cannot predict, classify things that it did not see before. Ti can.
Te has logic, measurement, contingency planning. In compsci terms it is a combo of a recursive depth-first search, logic and sensor data processing. It has rudimentary modeling abilities. It is quick so it probably utilizes a cache (hah!).
Ne, Ni are the ultimate non-deterministic generator of possibilities. They are probably "multi-threaded", as they generate many possibilities, sometimes blindly, these many possibilities can be executed in parallel. Even then however, their job might take a long time to finish, which must be why Ni,Ne is known to keep working even when a person is asleep, busy with other things. A "discovery" popping into a scientist's head is simply Ni, Ne finishing its work. There's nothing mysterious about it. Note: Generating possible solutions and verifying them are seperate tasks of course (per our P ≠ NP? discussion), Ne,Ni generate, Ti,Te verify.
Stereotypes
Knowing someone, at a certain level, is about being able to peg them. If you see behaviour X a hundred times, 101th time you expect it, somewhat different way -with some sauce-, then you feel like you know that person. Culturally, in US, and relationship-wise between subcultures, minorities and majorities, a form of this pegging happens all the time. Distance is a major factor in the country, so people need to form connection fast and efficiently over vast distances [1], between varying subgroups; so categorizing someone becomes ever more important.
Surely stereotypes can have a bad side, US culture balances that through its "letting go / prohibition" code.. This tug-of-war works fine on this issue, most of the time; The mainstream stance of prohibiting oneself on racial, stereotypical issues is the rule, while, as the exception, an undercurrent of comedy, art, silly talk between friends manages to play with this hot potato, dancing on the issue, and still make some substantial statements, while at the same time giving people a funny group to belong to.
In terms of comedy some of the best jokes I heard in US were on racial, stereotypical issues. It seems the more comical the stereotype is, the more it is embraced, and that perhaps pushes the uglier, bad forms of stereotyping away from society; Examples are many: Mexicans can't park, black people love fried chicken, etc. This process is part of "creating culture" in US. I once watched an Italian-American comedian in a comedy club, his jokes would start about himself, how guido his friends are, then move on to black men, then to oral sex, after which he would just drop the bomb: "Brothers won't eat that shit unless it's fried!". A comedy club full of all ethnicities would just explode in laughter.
Stop Trying To Make Money From Distribution
As Tim O'Reily said, this link sums up Holywood's piracy problem perfectly.
Before Internet distributing content was inefficient, hence distributors could provide a service by making the delivery of content just a tad more efficient. The problem is publishers also hooked their payment-receiving mechanism into this delivery as it was logical at the time; A needs product X, B delivers it, A pays to B before delivery, who passes the earnings onto C.
Fast forward to 2day. Free distribution of content is highly efficient -- noone can beat it and provide a "service" by replacing this. Unfortunately, now content producers lose their "hook", the place where they inserted their payment receiving step.
This is why I've been saying, a new payment mechanism must assume distribution is now seperate from payment mechanism, for good. Since legal enforcement is out of question (Net distribution is, well.. distributed, but enforcement is concentrated, 3rd wave vs 2nd wave, latter loses) we need to make it very easy to indicate interest, "likes" in a product. If given the chance, I am sure people will indicate their likes, dislikes; in fact, there is nothing people like to do more in their leisure time.
Free market, capitalism worked because it was mostly based on what was natural. In this day and age sharing and distribution of content is natural. This is the new "constant" and any successful system needs to take that constant into account, rather than fighting it. You can try to fight it of course but the natural will kick your ass. Just ask the Soviets. However, with one simple change of viewpoint, free distribution of content can be seen as a major service, a benefit to all consumers and content creators alike.
I am not saying my proposal is the best, or the only method. I was simply trying to demonstrate an alternative that takes the new constant into account.
Stretched Thin
To stretch this far … modernity must necessarily be culturally thin. … It is a generic culture, this culture of the television age, of asphalt, advertising, uniformity, and waste. And those who feed on it, those who live by it, become generic people who also are thin, who stretch wide and belong to nowhere in particular.
-- David Wells
Larry Wasserman: "A World Without Referees.. Our current peer review is an authoritarian system resembling a priesthood or a guild. It made sense in the 1600’s when it was invented. Over 300 years later we are still using the same system [..] If we used the same printing methods as we did in 1665 it would be considered laughable. And yet few question our ancient refereeing process. [..] I argue that our current peer review process is bad and should be eliminated.
The refereeing process is very noisy, time consuming and arbitrary. We should be disseminating our research as widely as possible. Instead, we let two or three referees stand in between our work and the rest of our field. I think that most people are so used to our system, that they reflexively defend it when it is criticized. The purpose of doing research is to create new knowledge. This knowledge is useless unless it is disseminated. Refereeing is an impediment to dissemination.
Every experienced researcher that I know has many stories about having papers rejected because of unfair referee reports. Some of this can be written off as sour grapes, but not all of it. In the last 24 years I have been an author, referee, associate editor and editor. I have seen many cases where one referee rejected a paper and another equally qualified referee accepted it. I am quite sure that if I had sent the paper to two other referees, anything could have happened. Referee reports are strongly affected by the personality, mood and disposition of the referee. Is it fair that you work hard on something for two years only to have it casually dismissed by a couple of people who might happen to be in a bad mood or who feel they have to be critical for the sake of being critical?
Some will argue that refereeing provides quality control. This is an illusion. Plenty of bad papers get published and plenty of good papers get rejected. Many think that the stamp of approval by having a paper accepted by the refereeing process is crucial for maintaining the integrity of the field. This attitude treats a field as if it is a priesthood with a set of infallible, wise elders deciding what is good and what is bad. It is also like a guild, which protects itself by making it harder for outsiders to compete with insiders.
We should think about our field like a marketplace of ideas. Everyone should be free to put their ideas out there. There is no need for referees. Good ideas will get recognized, used and cited. Bad ideas will be ignored. This process will be imperfect. But is it really better to have two or three people decide the fate of your work?
Young statisticians (and some of us not so young ones) put our papers on the preprint server arXiv (www.arXiv.org). This is the best and easiest way to disseminate research. If you don’t check arXiv for new papers every day, then you are really missing out [..]
When I criticize the peer review process I find that people are quick to agree with me. But when I suggest getting rid of it, I usually find that people rush to defend it. Is it because the system is good or is it because we are so used to it that we just assume it has to be this way? In three years we will reach the 350th birthday of the peer review system. Let’s hope we can come up with better ideas before then"