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Adams vs. Jefferson: The Birth of Negative Campaigning in the U.S.

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Negative campaigning in the United States can be traced back to John Adams and Thomas Jefferson. Back in 1776, the dynamic duo combined powers to help claim America's independence, and they had nothing but love and respect for one another. But by 1800, party politics had so distanced the pair that, for the first and last time in U.S. history, a president found himself running against his VP.

Things got ugly fast. Jefferson's camp accused President Adams of having a "hideous hermaphroditical character, which has neither the force and firmness of a man, nor the gentleness and sensibility of a woman." In return, Adams' men called Vice President Jefferson "a mean-spirited, low-lived fellow, the son of a half-breed Indian squaw, sired by a Virginia mulatto father." As the slurs piled on, Adams was labeled a fool, a hypocrite, a criminal, and a tyrant, while Jefferson was branded a weakling, an atheist, a libertine, and a coward. Even Martha Washington succumbed to the propaganda, telling a clergyman that Jefferson was "one of the most detestable of mankind."

Jefferson Hires a Hatchet Man

Back then, presidential candidates didn't actively campaign. In fact, Adams and Jefferson spent much of the election season at their respective homes in Massachusetts and Virginia. But the key difference between the two politicians was that Jefferson hired a hatchet man named James Callendar to do his smearing for him. Adams, on the other hand, considered himself above such tactics. To Jefferson's credit, Callendar proved incredibly effective, convincing many Americans that Adams desperately wanted to attack France. Although the claim was completely untrue, voters bought it, and Jefferson won the election.

Playing the Sally Hemings Card

Jefferson paid a price for his dirty campaign tactics, though. Callendar served jail time for the slander he wrote about Adams, and when he emerged from prison in 1801, he felt Jefferson still owed him. After Jefferson did little to appease him, Callendar broke a story in 1802 that had only been a rumor until then—that the President was having an affair with one of his slaves, Sally Hemings. In a series of articles, Callendar claimed that Jefferson had lived with Hemings in France and that she had given birth to five of his children. The story plagued Jefferson for the rest of his career. And although generations of historians shrugged off the story as part of Callendar's propaganda, DNA testing in 1998 showed a link between Hemings' descendents and the Jefferson family.

0705-cover.jpgJust as truth persists, however, so does friendship. Twelve years after the vicious election of 1800, Adams and Jefferson began writing letters to each other and became friends again. They remained pen pals for the rest of their lives and passed away on the same day, July 4, 1826. It was the 50th anniversary of the Declaration of Independence.


This article was written by Kerwin Swint and originally appeared in mental_floss magazine. Mr. Swint is a professor of political science at Kennesaw State University and the author of Mudslingers: The 25 Dirtiest Political Campaigns of All Time (Praeger, 2006). Jefferson/Adams image via Neatorama.

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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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