Mountains out of Molehills : a visualization by David McCandless of media scares from the Y2K bug to swine flu.
More interesting are the seemingly perennial hype like violent video games and autism vaccinations. The latter seems to be characterized by mostly spikes corresponding to big news developments; it’s hard to tell anecdotal stories about it without some other novelty to glam it up.
On the other hand, violent video games seem to be a more constant source of stories, due to them usually building off of already-sensational stories of youth violence that happen at a steady clip year-round. But there is a seasonal dip, as the stories drop to near-nothing during the summer; I’m unsure as to why this is the case.
Maybe it’s because video games aren’t conflicting with schoolwork during the summer, so it’s harder to leverage already-existing anxieties to scare parents. Maybe it’s because most scary youth violence that can be blamed on video games takes place at schools. Maybe the local news is too busy scaring us with sharks and warm-weather threats.
I need a few more pretty graphs to confirm/deny any theories. :(
Sally Forth a few Sundays back, reinventing Gravity’s Rainbow for the newspaper comic page. (via The Millions)
3D Mapping the World, Cheaply
Computer graphics these days are expensive; only two of the twenty-five most expensive movies ever came out before the mid-nineties, even adjusting for inflation. While computer power is getting ever-cheaper, the artists aren’t. Scripts are only getting wilder, and audiences demand more and more spectacular films with every passing summer. And as these graphics are already prohibitive for movies, they’re way outside the potential budget of any academic or non-profit projects. Is there any way out of this bind?
One field of computer graphics promises to take advantage of computing power and turn it towards making artists’ jobs easier. Called image-based modeling and rendering, the essential insight of this movement is pretty simple to understand: if we can take a 3D model in the computer and turn it into a 2D image for our movie-screen, can we figure out a way to do it the other way around? Can we turn a 2D image into a 3D model, automatically?
One early effort in the field was The Campanile Movie, made by Paul Debevec using techniques from his UC Berkeley Ph.D. thesis. Using a rough 3D model of the campus campanile tower and some images they took of it, they were able to project the color, texture, and finer qualities from the photos onto the model. It’s a similar process to how you can use an overhead projector to blow up an image so you can copy it in larger-scale on a wall. Debevec baked these projected details onto the rough model, giving him a far better model that he could then have the computer view from any angle he wanted. The technique was so successful - see the movie for examples - that it was later commercialized for use in an obscure art-film called The Matrix.
That kind of image-based modeling was useful, but only if you built the 3D model first and then painstakingly reconstructed the angles and distances of the reference photos you took of the real-life object. Finer variations used 3D scanners to quickly computerize models and sculptures built by artists, which is what Weta Workshop used for some effects in the Lord of the Rings films. The technology even was useful outside of films, with Google using large 3D scanners to quickly model cities (and a Radiohead music video). As with any technologies, it had its limits; John Gaeta tried using the technique on Keanu Reeves’ face, but with disappointing results.
But 3D scanners might not be necessary for the newest wave of innovation. Microsoft’s Photosynth technology (appearing about 2:40 into this impressive video) gives a very rough idea of what the shape of a building is like, using certain targeted commonalities to understand where each photo of is in relation to the next. The object you’re viewing looks like a collection of dots, but from most viewpoints photos will fade in to show you what someone’s photo looked like from that angle. This is useful for organizing photos, but can’t give us anything more than a rough, stuttering fly-around.
Now that we know how to locate where images were taken from and what they’re taken of, the obvious next step is to try and reconstruct a serious 3D model of the object; that’s where this project comes in. The University of Washington’s GRAIL lab - the same group that produced the precursor to Photosynth - has come up with a way to extract finer 3D model information from hundreds of thousands of images, producing a 3D cloud that looks roughly like the real thing! With just a flickr search, a collection of careful algorithms, and a day or so of cluster computing time, they can build an entire city without any human intervention.
It’s just a matter of time before computer scientists figure out how to create a 3D model good enough that you can start directly mapping the image data onto its surface, automatically creating an image as good as the The Campanile Movie out of a bunch of photos you found on the internet. And there are still limitations that stand out as Hard Problems to Overcome: how to deal with radically different lighting at different times of day and night, how to deal with moving objects, and how to make this feasible for sets that don’t have thousands of images to work with. But this newest step still looks incredibly promising, especially if it finally justifies the endless numbers of photo albums on Facebook.
Deontology v. Consequentialism
Last week dailymeh wrote an excellent post examining the two opposing schema of rule-based morality and consequence-based morality that seem to compete when we make a decision. They’ve been distinct schools of thought for centuries, but there’s recent evidence that shows both find distinct force in the brain’s reasoning process.
But if we rush to declare this a “dialectic,” we ignore the third major school of thought in modern ethical theory: virtue ethics, which says the most important part of morality is neither the rules followed nor the results engendered, but the character of the person making the decision. It’s actually the oldest* of the three major schools, appearing in Plato’s Republic and other Greek writings. It disappeared for a while when deontological and consequentialist ethics were articulated, but has roared back into the philosophical mainstream in the last half-century. (It’s also my favorite.)
As always, the Stanford Encyclopedia of Philosophy has excellent entries on deontology, consequentialism, and virtue ethics - as well as some sketchy hybrids like rule consequentialism.
* Older works like the Old Testament espouse rule-based, deontological morality (like do not kill, do not have any other gods before me, etc.). But it doesn’t become philosophically articulated until approximately Much Later A.D., whereas we see attempts at argument in virtue ethics from the very beginning.
From the NY Times, news that a smarter-than-average bear has learned to open bear-proof containers.
Just goes to show that COLBERT WAS RIGHT!
Automated, high-speed stock trading on the rise
One of the more interesting trends in stock market trading these last few years has been so-called “high-frequency trading,” which uses the combination of sophisticated high-speed computers and a firehose of information about the market to execute trading strategies that would be completely impossible by hand.
Using a preferred connection, complicated algorithms can detect subtle trends in the market and do things like try to lead the curve in real-time, or subtly probe the other traders to see what their limits were. It’s the latter trick that has led some traders to cry foul, as the algorithms propose trades and cancel them as fast as possible, just to try and figure out the behavior of other individual traders. It’s a pattern of behavior specifically designed to stretch prices as far as possible, at the expense of liquidity and other attributes that are healthy for the stock market to possess.
And there’s a further concern: as an anonymous hedge fund manager notes in a sprawling and fascinating interview, most of these automated traders are running algorithms based off the same theories about the stock market; if one hits a blind-spot, they all hit a blind-spot. He tells a story from August of 2007:
The problem is that the DNA of a lot of these models is very, very similar, it’s like an ecosystem with no biodiversity because most of the people who do [statistical arbitrage] can trace their lineage, their intellectual lineage, back to four or five guys who really started the whole black box trading discipline in the ’70s and ’80s. And what happened is, in August, a few of these funds that have big black box trading books suffered losses in other businesses and they decided to reduce risk, so they basically dialed down the black box system. So the black box system started unwinding its positions, and every black box is so similar that everybody was kind of long the same stocks and short the same stocks. So when one fund starts selling off its longs and buying back its shorts, that causes losses for the next black box and the people who run that black box say, “Oh gosh! I’m losing a lot more money than I thought I could. My risk model is no longer relevant; let me turn down my black box.” And basically what you had was an avalanche where everybody’s black box is being shut off, causing incredibly bizarre behavior in the market.
We had a loss over the course of like three days that was like a ten-sigma event, meaning, you know, it should never happen based on the statistical models that underlie it. Why? Because the model doesn’t assume that everybody else is trading the same model as you are. So that’s sort of like a meta-model factor. The model doesn’t know that there are other black boxes out there.
Building a Supercomputer Brain
A neat article from Jonah Lehrer detailing the joint venture with IBM that’s attempting to simulate a brain within a computer. This isn’t any ordinary simulation, though, for a few different reasons:
- Bottom-up, with the team simulating the fundamental building-blocks of the brain to see if they can get accurate enough that higher-level behavior emerges from the cognitive soup.
- Brutally realistic, with the team systematizing old experimental data to get the best possible evidence as to how those building blocks actually operate.
- Comprehensive, with the team eventually aiming for an actual simulation of a rat brain.
Most of the efforts these days have been taking high-level behavior and trying to guess at deeper features that would generate this behavior. While this is more immediately useful (see behaviorism and the rest of psychology), it can only dig so deep. Bottom-up simulations of the brain allow us to put ever-rising computing power to good use.
Additionally, it gives us the best chance at finally getting those dualists to see the light and become full-blown physicalists - putting one more nail into the coffin of metaphysics. Yes, I still hold grudges from my Philosophy of Mind class and will have my vengeance against John Searle in this world or the next.
"Why markets can't cure healthcare" by Paul Krugman
In short:
- Prices are either unpredictably cheap or expensive, which means insurance is the only realistic way for most people to pay for it.
- Insurance is incentivized to deny people care, which they do by refusing claims and not enrolling those with pre-existing conditions.
- But when insurance tries to cut costs responsibly - by discouraging ineffective treatments and so forth - they don’t have the trust from the public to do just that since we know about their incentive structure and regard every cost-cutting measure as morally cruel.
#1 means insurance is necessary, which walks us into the chicken-and-egg bind presented by #2 and #3. When it comes to cost-cutting in the current system, those covered by insurance perceive themselves to be bearing all the risk with promise of little reward in reduced premiums.
A public option would break this stalemate by combining the incentive and the costs into the same pool; any money saved in health-care would be returned to those the insurance covers, rather than a third-party stockholder. Additionally, by cutting costs it would provide precedent that private insurers could point to when instituting similar prudent cost-cutting measures within their own systems.
