Christopher Nolan Helps Us Interpret <cite>Inception</cite>

Consider us incepted. Ever since Christopher Nolan’s blockbuster hit theaters in July, we’ve been trying to suss out dream from reality. Now that we can bring the movie home, we can put our freeze-frame thumb to use. (Haven’t seen the movie? Stop reading. This is one big spoiler.) Nolan specializes in puzzles, and Inception is no exception. The trick isn’t the plot—come on, it wasn’t that complicated. The challenge is picking out Nolan’s lies. Does hero Dom Cobb’s totem tell the truth about whether he’s dreaming? Is the sequence in Mombasa just good action or good action in a paranoid dream? Below, our take on what’s really going on. To make sure we haven’t lost our minds, we let Nolan himself weigh in. As they say in Inception, the only way forward is downward—so into the rabbit hole we go.

Use the scrollbar below to view all layers of Inception.

Illustrations: Luke Shuman

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Teen Mathletes Do Battle at Algorithm Olympics

Neal Wu’s last chance for international glory, and maybe America’s, too, begins with a sound like a hippo crunching through a field of dry leaves—the sound of 315 computer prodigies at 315 workstations ripping into 315 gray envelopes in unison. “You have five hours,” a voice booms across the packed gymnasium. “Good luck.”

At his desk on the gym floor, Wu, age 18, pushes his glasses up on his nose and squints. He shouldn’t need luck. This is a coding competition—the International Olympiad in Informatics, held in August at the University of Waterloo in Ontario, Canada—and Wu is one of the world’s top competition programmers.

Gold medals awarded at the International Olympiad in Informatics (1999-2009)

He just graduated from Baton Rouge Magnet High School in Louisiana; his parents are chemical engineers originally from Shanghai, although Wu was born in the US. In seventh grade, he took first place in a nationwide contest for middle schoolers called Mathcounts. (There’s a Neal Wu fan club on Facebook that celebrates his “awesome math skills.”) Yet according to Rob Kolstad, the US team’s 57-year-old head coach, Wu is merely “very good” at math. His true gift is for creative problem-solving with code. In 2008, the first year he competed at the IOI, he finished 10th out of 300 contestants. In 2009, he moved up to seventh place. Since then, he has competed in six coding contests run by Kolstad’s organization, the USA Computing Olympiad; he won three of them with perfect scores. Wu has the relaxed disposition of a star athlete; he’s confident without ever letting on that he is America’s Great Nerd Hope. “I hate to say he’s the Tiger Woods of computer programming,” Kolstad says, “but he shares the properties of cool, calm under pressure, and consistent, consistent performance.”

Cool or no, there are a lot of expectations on Wu as he shuffles through the contents of his gray envelope. Four stapled packets of paper. Four word problems designed to test programming prowess—specifically, the ability to crunch incredibly huge and complex data sets in seconds. For each problem, Wu first has to choose an algorithm, or series of computational steps. Then he has to code it. Wu’s coaches have drilled into his brain 16 standard algorithms with names like Two-Dimensional Convex Hull, Greedy, Eulerian Path, and Knapsack—an arsenal of mathematical machetes for hacking through thickets of numbers—and in Wu’s years of coding he has flexed and massaged the algorithms into no fewer than 100 subtle variations. But what makes IOI so difficult, unpredictable, and yes, even dramatic is that competitors like Wu may have to invent and code their own ad hoc algorithms on the spot. One-of-a-kind solutions to one-of-a-kind problems. From scratch. In five hours.

It’s grueling work, so Wu starts out slowly. He flips through the problem sheets, scribbling an occasional note with his mechanical pencil. The dominant sound in the gym changes from the shuffling of paper to the clacking of keys, but Wu resists the urge to type right out of the gate. “Typing is hypnotic,” Kolstad says emphatically. “When you’re typing, you’re not solving problems.”

But Wu’s nemesis, the Boy Wonder of Belarus, does not subscribe to this theory.

A tall kid with skinny arms, short brown hair, and a bashful smile, Gennady Korotkevich started competing at IOI when he was 11. When Wu was 11, he didn’t even know about programming. At last year’s IOI in Bulgaria, Korotkevich upset Wu and everyone else to take first place, becoming the youngest winner in the contest’s 20-year history. This year Korotkevich is back again, at the ripe age of 15, looking to deprive Wu of his last shot at winning IOI. Next year Wu will be in college and therefore ineligible.

Clockwise from top left: A printout of the Maze problem; Gennady Korotkevich of Belarus; work in progress on Maze; American Neal Wu.
Photo: Michael Schmelling

Their styles couldn’t be more different. While Wu is relaxed and thoughtful, Korotkevich is a jackrabbit. “My parents are programmers, and now I like it as well,” he says in tentative English. Unlike the sociable Wu (who interned at Facebook last summer), Korotkevich squirms when I talk to him about his abilities, insisting he’s nothing special. At IOI, he sticks close to his Belarus teammates and coaches. The gossip at IOI is 40 percent about the word problems, 10 percent about which country’s coaches have the best liquor (Canada, hands down), and 50 percent about Gennady Korotkevich. Ask the kids who’s going to win this year and regardless of whether they’re Kazakh or Japanese, Swiss or Egyptian, they’ll invariably grunt, “Belarus, Belarus.” And then they’ll start laughing, as if to say, haven’t you been paying attention?

This morning, Korotkevich began typing five minutes and 40 seconds after the competition began. Like several of the elite competitors at IOI, he can code as fast as he can touch-type. Three minutes later, Korotkevich completed his first program: a mere 22 lines of Pascal.

The three approved IOI programming languages are Pascal, C, and C++. The Western kids, including Wu, tend to use C++, the most modern and streamlined of the three. But Pascal still has a following in Eastern Europe and Asia, even though coding in it is like “building a car with just a screwdriver and a wrench,” says Troy Vasiga, this year’s IOI chair.

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<em>Green Lantern</em> Keeps Comics Buzzing on the Big Screen

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Build an Igloo

If you're planning an excursion into the frozen tundra, learn a few tricks from those who've lived there the longest. The Inuit of Northern Canada have been making shelters out of snow and ice as long as the white stuff has been around.

An igloo is warmer and more durable than a tent, providing better insulation from the harsh winter elements. Here's a guide to building an Inuit snow house.

This article is part of a wiki anyone can edit. If you have advice to add about building an igloo, log in and contribute.

Watch this: http://www.nfb.ca/film/How_to_Build_an_Igloo/

It will probably take you five or six hours to build an igloo that sleeps two adults comfortably.

All you need is a large knife (a saw, a shovel may help) and a strong back. Any shovel will do, but you'll have an easier time if you use a small, sturdy snow shovel, like the kind found at outdoor and camping supply stores.

To replicate the dense, wind-packed snow of Inuit country, shovel it into a 2-foot-high, 10-foot-square sheet cake and stomp it down. Use snowshoes to stomp, if you have them. Wait a few hours, allowing the ice crystals to interlock and strengthen.

Using a knife (carpenter's saw or snow saw), cut blocks roughly 2 feet long, 1 foot wide, and 1.5 feet high. Ideally they should be approximate 4" thick. Think of them as big, cold Legos.

Mark out a ring 6 feet across and begin stacking blocks in an ascending spiral. Cut a slope on the first two blocks to start the slope. Use larger blocks at the bottom and smaller blocks at the top. Shave a slope into the top surface of each block so the wall curves inward as it rises. The best way to ensure a fit is to place a block and then cut though the joint. Work from the inside.

Once the dome is underway, lower the floor of your igloo to give you more headroom, then level it out.

Place the last few blocks on top with the help of somebody standing inside. You can spear the last few blocks on a knife to stabilize them. The anchor block may be cut bigger than the last hole and extended out through the hole (secured at the point of a knife) and cut with another knife to fit.

Smooth out the blocks inside and out. Push the excess snow into the joints between blocks, sealing any holes or cracks.

Cut a doorway. Additionally, you can help protect yourself from the wind by digging down into the snow to make an entrance, so that you duck down to enter, then stand up inside.

Poke a hole in the dome for air. To brighten up the joint, replace one block with pure ice — voilà, a picture window!

Originally submitted by Wired contributor Bob Parks

This page was last modified 07:11, 6 December 2010 by llm1. Based on work by ralfred and howto_admin.

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Science Funding for the Little Guys

Illustration: Ulises Farinas

The institutions that foot the bill for scientific research tend to be best at writing big checks for big projects. Now a bunch of nonprofits are trying to fund the little guys, asking for small donations to small projects. A focus on transparency—researchers must update donors with progress reports—could help get the public invested in science with their hearts as well as their wallets. Here’s a look at the new funds.

How it works: Microdonations to individual projects or organizations, with a time limit on the fund-raising. Projects that don’t hit their targets have their funds redistributed.
What makes it different: FundScience takes donations from individuals and organizations alike.
Sample project: Researchers at the Center for Genomic Sciences are looking to study a nasty strain of antibiotic-resistant pneumococcus bacteria—the most common cause of bacterial meningitis.
Amount raised: $2,500
Still to raise: $22,500

How it works: Microdonations to individual projects until funding goals are met.
What makes it different: A focus on research that could benefit people living in poor communities or the developing world. A scientific advisory board reviews all grant proposals.
Sample project: A testing facility for inexpensive solar panels, to be built on the UC Berkeley campus.
Amount raised: $25,351
Still to raise: $47,229

How it works: Microdonations with a financing deadline. If a project doesn’t meet its funding target, donors can choose to transfer their contributions to other research.
What makes it different: As part of its effort to make science accessible to all, SciFlies pairs researchers with professional science writers to make their proposals easier to understand.
Sample project: A network of robotic sensors for Tampa Bay to measure chemical changes in the water caused by flushed-away pharmaceuticals.
Amount raised: $0
Still to raise: $12,000

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Calling All Computer Geeks: Help NASA Explain Dark Energy

If you can teach computers to learn, NASA needs your help.

Cosmologists hope gamers, programmers, computer scientists and geeks-of-all-trades can help them identify evidence of dark matter. An international group of astronomers are hosting a competition, called GREAT10 (for GRavitational lEnsing Accuracy Testing), to come up with better ways to analyze distorted images of galaxies — the signatures of invisible dark matter lurking in the universe.

Massive clumps of matter can act as a giant cosmic magnifying glass, distorting space-time in their immediate vicinity. Light traveling through the matter clump is warped and distorted, a phenomenon called gravitational lensing.

Sometimes the distortions are obvious, like in the Hubble image of a distant galaxy cluster above. But sometimes they’re too subtle to be picked out by human eyes, and can even be confused with noise from the telescope used to take the galaxies’ picture.

So cosmologists have turned to machine learning algorithms that teach computers to recognize patterns.

“We’re trying to teach computers to pick out the correct shape given all sorts of other noise around the galaxy’s shape,” said NASA cosmologist Jason Rhodes, who is helping to organize the challenge. “We have our ideas as a community about how to do this, but we realized a few years ago that it was quite possible there were ideas we weren’t familiar with.”

The competition is designed to bring fresh ideas from machine learning and computer science experts. But the challenge is open to anyone.

“The image manipulation software and techniques used in gaming and some digital cameras are very similar,” said astrophysicist Thomas Kitching of the University of Edinburgh, which is helping to sponsor the event. “Anyone with experience in image manipulation and software development would be in a good position to enter the competition.”

Rhodes compares GREAT to other citizen science and engineering challenges, like the X-Prize private spaceflight competitions or the Netflix Prize to improve the movie rental website’s recommendation algorithms. Those challenges promised million-dollar prizes, which is beyond the cosmology community’s budget. But the GREAT10 winner will probably get an iPad or a Mac laptop.

And the real grand prize is helping to solve one of the trickiest and most fundamental puzzles in astronomy: What is the universe made of?

Ultimately, the computer programs developed for the GREAT challenge will be used to help unmask dark matter and dark energy, the mysterious stuff that makes up 95 percent of the universe.

By studying slightly distorted galaxies, scientists can make detailed maps of dark matter, the stubbornly invisible stuff that makes up 24 percent of the universe and makes itself known through gravitational tugs on regular visible matter. Knowing where the dark matter is and how it changes over time will help astronomers decipher dark energy, an even more mysterious substance that makes up 72 percent of the universe.

“The most exciting thing about this is that we are taking an interdisciplinary approach to one of the most pressing problems in all of science,” Rhodes said. “The ultimate goal here is really to develop methods for studying the composition of the universe and the ultimate fate of the universe. People who haven’t spent their lives studying cosmology can make a real contribution via the GREAT10 challenge.”

Image: Light bends around the massive galaxy cluster Abell 2218 in this image from the Hubble Space Telescope. Credit: Andrew Fruchter (STScI) et al., WFPC2, HST, NASA

See Also:

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Dec. 3, 1984: Bhopal, 'Worst Industrial Accident in History'

1984: Poison gas leaks from a Union Carbide pesticide factory in Bhopal, India. It spreads throughout the city, killing thousands of people outright and thousands more subsequently in a disaster often described as the worst industrial accident in history.

Union Carbide chose Bhopal, a city of 900,000 people in the state of Madhya Pradesh, because of its central location and its proximity to a lake and to the country’s vast rail system.

The plant opened in 1969 and produced the pesticide carbaryl, which was marketed as Sevin. Ten years later the plant began manufacturing methyl isocyanate, or MIC, a cheaper but more toxic substance used in the making of pesticides.

It was MIC gas that was released when water leaked into one of the storage tanks late on the night of Dec. 2, setting off the disaster. Gas began escaping from Tank 610 around 10:30 p.m., although the main warning siren didn’t go off for another two hours.

The first effects were felt almost immediately in the vicinity of the plant. As the gas cloud spread into Bhopal proper, residents were awakened to a blinding, vomiting, lung-searing hell. Panic ensued, and hundreds of people died in the chaotic stampede that followed.

An exact death toll has never been established. Union Carbide, not surprisingly, set the toll on the low end at 3,800, while municipal workers claimed to have cleared at least 15,000 bodies in the immediate aftermath of the accident. Thousands have died since, and an estimated 50,000 people became invalids or developed chronic respiratory conditions as a result of being poisoned.

Regardless of the numbers, all evidence pointed to Union Carbide and its Indian subsidiary (as well as the Indian government, its partner in the factory) being responsible for what occurred — mainly through negligence. Despite the extreme volatility and toxicity of the chemicals in use at the factory, safeguards known to be substandard were ignored rather than fixed.

In the subsequent investigations and legal proceedings, it was determined, among other things, that:

Staffing at the plant had been cut to save money. Workers who complained about codified safety violations were reprimanded and, occasionally, fired.No plan existed for coping with a disaster of this magnitude.Tank alarms that would have alerted personnel to the leak hadn’t functioned for at least four years.Other backup systems were either not functioning or nonexistent.The plant was equipped with a single backup system, unlike the four-stage system typically found in American plants.Tank 610 held 42 tons of MIC, well above the prescribed capacity. (It is believed that 27 tons escaped in the leak.)Water sprays designed to dilute escaping gas were poorly installed and proved ineffective.Damage known to exist to piping and valves had not been repaired or replaced, because the cost was considered too high. Warnings from U.S. and Indian experts about other shortcomings at the plant were similarly ignored.

The aftermath of the disaster was almost as chaotic. Union Carbide was initially responsive, rushing aid and money to Bhopal. Nevertheless, faced with a $3 billion lawsuit, the company dug in. It eventually agreed to a $470 million settlement, a mere 15 percent of the original claim. In any case, very little money ever reached the victims of the disaster.

Union Carbide CEO Warren Anderson went before Congress in December 1984, pledging his company’s renewed commitment to safety. That promise rang hollow in India — and probably to Congress as well.

Anderson was subsequently charged with manslaughter by Indian prosecutors but managed to evade an international arrest warrant and disappeared. Investigators from Greenpeace, which has kept up an active interest in the case, found Anderson in 2002, alive and well and living comfortably in the Hamptons. India issued an arrest warrant for Anderson in 2009, but the United States has shown no inclination to hand him over to Indian justice.

Union Carbide, meanwhile, was acquired by Dow Chemical in 2001, which refused to assume any additional liability for Bhopal, arguing that the debt had already been paid through various court settlements. It did go on to settle another outstanding claim against Union Carbide, this one for $2.2 billion made by asbestos workers in Texas.

In June 2010, seven former employees of Union Carbide’s Indian subsidiary were found guilty of death by negligence. They were fined about $2,000 each and sentenced to two years’ imprisonment, then released on bail.

The victims of the disaster, those who live on, continue dealing with various health problems — including chronic respiratory problems, vision problems and an increased incidence of cancer and birth defects — and an environment that remains contaminated to this day.

Source: Various

Photo: Wahid Khan, pictured here 10 years after the 1984 Bhopal disaster, survived the toxic gas exposure but was left permanently blind.
Reuters/Corbis

This article first appeared on Wired.com Dec. 3, 2008.

See Also:

Wikipedia Sleuths Win Journalism Award for Wired.comJan. 22, 1984: Dawn of the MacJan. 24, 1984: Birth of the Cool (Computer, That Is)April 11, 1984: Shuttle Makes House Call, Repairs SatelliteApril 23, 1984: AIDS Virus Disclosed, and a Premature Promise MadeSept. 10, 1984: DNA Leaves Its PrintOct. 20, 1984: An Aquarium for the Ages OpensNov. 20, 1984: SETI Seekers Find a HomeDec. 3, 1967: Patient Dies, but First Heart Transplant a SuccessDec. 3, 2001: Segway Starts Rolling

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