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Constantin Film International GmbH and Impact Pictures (Pompeii) Inc. All rights reserved

Expert Q&A: How Close Does Pompeii Reflect Reality?

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Constantin Film International GmbH and Impact Pictures (Pompeii) Inc. All rights reserved

In Paul W.S. Anderson’s Pompeii—in theaters now—Kit Harington and Emily Browning play a couple of star-crossed lovers in 79 A.D. whose forbidden relationship is the most minor of problems: The city they know and love is about to come crashing down, literally, as Mount Vesuvius starts spitting lava.

Like any good Hollywood disaster flick worth its ticket price, Pompeii’s filmmakers employed a fair amount of creative license. But Dr. Rosaly M. Lopes-Gautier, Senior Research Scientist and Manager of Planetary Science at NASA’s Jet Propulsion Laboratory and author of The Volcano Adventure Guide, says there’s a lot the movie gets right, scientifically-speaking. We pressed her for details. 

Among your many other achievements, you’re one of the world’s leading volcano experts. So—scientifically speaking—what parts of a volcanic eruption, and the eruption of Mount Vesuvius in particular, does Pompeii get right?
They got the sequence of events right: the fact that there were earthquakes before the main eruption, that a big explosion happened during the day but pyroclastic flows [rapidly-moving flows of rock and hot gasses] only reached Pompeii much later (in the movie, it’s during the night; in reality, it was early the next morning). The explosion cloud, the pyroclastic flows, [and] earthquakes, were all done very realistically.

Which aspects are most clearly a case of creative license?
There was pumice rock fall but no fiery bombs, which don’t happen in that type of very explosive eruption. However, the rock and pumice fall did destroy structures and caused fires (probably from overturned oil lamps). The lava lake in the crater was artistic license to convey the idea of magma coming up without the people realizing. The tsunami in the movie was larger than the one reported, and in reality the tsunami didn’t move ships in the city.

What’s the one thing you would have done differently?
I’d probably have made the tsunami less dramatic. However, this is a movie drama, not a documentary, so I think artistic license is perfectly fine.

Could the events of Aug. 24, 79 A.D. happen at Mount Vesuvius again?
Yes, though the eruptions of Vesuvius are not generally as large as the 79 A.D. one. Vesuvius tends to erupt in cycles, and the first eruption in the cycle is the largest. 79 A.D. was the opening of a new cycle, so was the large eruption of 1631.

What are the factors that could contribute to that being a reality?
It seems that the longer the volcano rests between cycles, the larger the initial eruption can be. The end of the last cycle was in 1944, with a not particularly violent eruption. Vesuvius could rest for many years before the next one.
 
What might the potential impact of that look like?
There are over one million people living near the volcano today. Potentially, the impact could be much larger than that of the 79 A.D. eruption. However, the volcano is very well monitored, so there would be warning. 

What are some of the other most potentially dangerous volcanoes around the world?
Many of the volcanoes in Indonesia, the Philippines, Japan, and other places around the “ring of fire” of the Pacific are potentially very dangerous, as they can have violent explosive eruptions such as Vesuvius did in 79 A.D., or even more violent. The most hazardous volcano in the U.S. is Mt. Rainier, although Yellowstone has the potential for catastrophic eruptions. When we consider volcanic hazard, we look at the probability of the volcano erupting in the near future, such as the next few decades, and the impact to human life and property. Even a not very large eruption from Mt. Rainier could cause ice in glaciers to melt, creating devastating mudflows.
 
What are three facts about volcanoes that most people don’t know?
1. Volcanoes don’t suddenly erupt without any warning. The movie correctly depicted that they had warning, because of the many earthquakes, but the people at the time did not connect the earthquakes to the volcano.

2. Pyroclastic flows and mudflows are much more dangerous than lava flows. Many lava flows travel slowly enough that you can get away from them, or even walk over them if the crust has cooled enough (cooled lava is a very good insulator, so the flow may still be molten underneath, but with a cool hard crust). Pyroclastic flows and mudflows travel much faster and often it is not possible to escape them using a car.

3. The most spectacular volcanoes to photograph and visit while in eruption are usually the least dangerous ones. For example, Stromboli in Italy, Yasur in Vanuatu, and Kilauea in Hawaii. They have either small explosions or no explosions at all, which makes them very tame as far as volcanoes go.

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iStock // Ekaterina Minaeva
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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Name the Author Based on the Character
May 23, 2017
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