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Courtesy of Barry Clifford

Barry Clifford on Finding the Santa Maria—and Why The Story Isn't Over Yet

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Courtesy of Barry Clifford

"I can't imagine what else it might be," Barry Clifford said earlier today at a press conference held at the New York headquarters of the Explorers Club. He was referring to the wreckage he discovered off the northern coast of Haiti that has been tentatively reported to be the remains of Christopher Columbus' flagship, the Santa Maria.

Clifford was all but adamant that this is the historic ship. "We're looking for a big pile of stones in a space the size of Yankee Stadium in clear water," he said of the search. "It's not nuclear physics." So why, then, had the ship gone undiscovered for over 500 years? Even Clifford didn't realize the wreck that he found and photographed in 2003 was the Santa Maria until recently.


All studies of Christopher Columbus rely on a detailed primary document: his diary. Like other explorers and archeologists, Clifford knew it would be the key to finding the Santa Maria: "[Columbus] wrote it knowing it would be scrutinized." And that instilled a very valuable sense of urgency.

At 11:00pm on Christmas Eve 1492, Columbus wrote that he went to sleep with the Santa Maria "standing" in the Bay of Campeche. An hour later, the ship ran ashore so quietly, according to Columbus, that no one on board even woke up.

Two things about the entry stood out: The first was Columbus' notion that the ship was standing still. "I knew after diving in this area that there’s no way you can stand still because of the current," Clifford said. The second thing that stood out was the relative silence of the crash, which would have been impossible had Columbus run aground on a coral reef. Clifford (and anyone else searching for the Santa Maria) knew they were looking for a sandy patch consistent with modern understandings of the currents around the coast.

And yet for years, excavators found nothing—because they were looking in the wrong place. Columbus wrote that the wreck was located one and a half leagues from La Navidad, the first European colony built in the "New World" in the days after the wreck using timber stripped from the ship. (Incidentally, La Navidad did not last long—when Columbus returned the following year, the fort was in ruins and the 39 men left behind had all been murdered by local tribes.) But one by one, targets (objects identified by magnetometer survey) at the correct distance from the assumed location were ruled out—until a proposition by the University of Florida's Dr. Kathy Deegan that put La Navidad two miles further west than originally thought.


That opened up a new range of possibilities, but Clifford still initially discounted the wreck that is now thought to be the Santa Maria when he first discovered it in 2003. He and his son photographed and surveyed everything at the site, but misidentified a long, tubular object.

"In 2012, I sat up in the middle of the night and realized, that's not a tube, that's a lombard," Clifford said, referring to a specific type of 15th century Spanish cannon known to have been aboard Columbus' ships. It was just the eighth of its kind found in the Americas and, after comparing photos from the wreck to research on lombards, represented the smoking gun in the mystery of the Santa Maria.


But the story is far from over. Clifford and his team returned to the site recently only to find many of the artifacts, including the telltale cannon, had been looted by what Clifford believes to have been opportunists from the Dominican Republic who got word of the valuable nature of the wreck. He calls this an "emergency situation"—especially since he was forced to leave the site unattended after contracting cholera.

Clifford expressed concern that Haiti is unprepared to take advantage of what could be a unique and valuable source of tourism and revenue. "It is a very important resource for Haiti and it has to be protected," he said. "But they need help."

Professor Charles Beeker of Indiana University will lead the excavation, but Clifford has hopes for an international effort to protect and preserve the wreck. He imagines that eventually a traveling exhibit can be brought to life showcasing the Santa Maria to the public, with proceeds benefiting Haiti.

SANTA MARIA PRESS VIDEO from Dov Freedman on Vimeo.

Password for the video: octoberfilms. All Photos Courtesy of Barry Clifford.

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iStock // Ekaterina Minaeva
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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Stephen Missal
New Evidence Emerges in Norway’s Most Famous Unsolved Murder Case
May 22, 2017
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A 2016 sketch by a forensic artist of the Isdal Woman
Stephen Missal

For almost 50 years, Norwegian investigators have been baffled by the case of the “Isdal Woman,” whose burned corpse was found in a valley outside the city of Bergen in 1970. Most of her face and hair had been burned off and the labels in her clothes had been removed. The police investigation eventually led to a pair of suitcases stuffed with wigs and the discovery that the woman had stayed at numerous hotels around Norway under different aliases. Still, the police eventually ruled it a suicide.

Almost five decades later, the Norwegian public broadcaster NRK has launched a new investigation into the case, working with police to help track down her identity. And it is already yielding results. The BBC reports that forensic analysis of the woman’s teeth show that she was from a region along the French-German border.

In 1970, hikers discovered the Isdal Woman’s body, burned and lying on a remote slope surrounded by an umbrella, melted plastic bottles, what may have been a passport cover, and more. Her clothes and possessions were scraped clean of any kind of identifying marks or labels. Later, the police found that she left two suitcases at the Bergen train station, containing sunglasses with her fingerprints on the lenses, a hairbrush, a prescription bottle of eczema cream, several wigs, and glasses with clear lenses. Again, all labels and other identifying marks had been removed, even from the prescription cream. A notepad found inside was filled with handwritten letters that looked like a code. A shopping bag led police to a shoe store, where, finally, an employee remembered selling rubber boots just like the ones found on the woman’s body.

Eventually, the police discovered that she had stayed in different hotels all over the country under different names, which would have required passports under several different aliases. This strongly suggests that she was a spy. Though she was both burned alive and had a stomach full of undigested sleeping pills, the police eventually ruled the death a suicide, unable to track down any evidence that they could tie to her murder.

But some of the forensic data that can help solve her case still exists. The Isdal Woman’s jaw was preserved in a forensic archive, allowing researchers from the University of Canberra in Australia to use isotopic analysis to figure out where she came from, based on the chemical traces left on her teeth while she was growing up. It’s the first time this technique has been used in a Norwegian criminal investigation.

The isotopic analysis was so effective that the researchers can tell that she probably grew up in eastern or central Europe, then moved west toward France during her adolescence, possibly just before or during World War II. Previous studies of her handwriting have indicated that she learned to write in France or in another French-speaking country.

Narrowing down the woman’s origins to such a specific region could help find someone who knew her, or reports of missing women who matched her description. The case is still a long way from solved, but the search is now much narrower than it had been in the mystery's long history.

[h/t BBC]