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"Black Friday"

Original image
Getty Images

“Black Friday”
Written by Donald Fagen and Walter Becker (1975)
Performed by Steely Dan

The Music

With songs about everything from flashy drug czars to downtrodden jazz musicians, Steely Dan have always cast their lyrical net far from the usual romantic fare of pop music. On one of the standout tracks from their 1975 album Katy Lied, they dug back to the 19th century to write about an infamous financial disaster. Not that it was straight history. Songwriters Donald Fagen and Walter Becker, true to their left-of-center muse, imagined a savvy investor who cashes out just before the crash and escapes to Australia to walk barefoot on the beach and watch the kangaroos.

“Black Friday” reached #37 on the charts. It also marked the debut of Michael McDonald as Steely Dan's background vocalist of choice. McDonald, who went on to fame with the Doobie Brothers and as a solo artist, would lend his distinctive voice to many more Dan tunes, including “Kid Charlemagne,” “I Got The News” and “Peg.”

The History

Today, we associate the term Black Friday with the day after Thanksgiving, and all its pre-Christmas shopping madness. But the original Black Friday was about something more dire and disastrous.

During the Civil War, both the Union and Confederate governments financed their military operations with “greenback” currency—that is, money not backed by gold or silver reserves. After the Union won, the government, under President Ulysses S. Grant, continued to pour huge amounts of greenbacks into reconstruction projects. The greenbacks were basically promissory notes. Backed by the “full faith” of the government, they would one day be redeemable for precious metal-backed currency. But by 1869, the value of the greenbacks had fallen to the point where people started to panic over the true worth of their savings and investments.

We're In The Money

Enter Jay Gould and James Fisk. Gould was a railroad tycoon and a financial speculator. Fisk, known as “Diamond Jim,” was a stockbroker and ruthless businessman. In 1868, the pair had used stock fraud and bribery to prevent Cornelius Vanderbilt from taking control of the Erie Railroad, which they owned. Now they set out to corner the gold market and cheat investors. They saw how the U.S. Treasury had been increasing the supply of gold to the market to regulate its price. Gould and Fisk figured they could buy massive quantities of gold, drive up its value and then sell it off for a huge profit.

To ensure their scheme didn't go awry, Gould and Fisk recruited another financier, Abel Corbin, who happened to be married to Virginia Grant, the President's sister. This allowed Gould and Fisk to meet Grant on several social occasions, which they used to argue against the sale of government gold. Grant listened politely, but didn't take them seriously. Corbin further exercised his insider status to influence Grant to appoint former Union army general Daniel Butterfield as assistant Treasurer. It would be Butterfield's job to manage the government's buying and selling of gold. With Corbin's help, Gould and Fisk bribed Butterfield to provide advance notice of any large government sell-off of gold.

As Gould and Fisk's scam continued, gold prices rose and stocks fell. By September 1869, the premium on gold was 30 percent higher than when Grant took office. Soon, bank runs were breaking out across the country, with depositors demanding gold on their greenbacks and threatening to hang bank managers if they didn't get it. In some cases, the army had to be called in to suppress violence. Grant had become increasingly suspicious of Corbin's interest in the gold market, but when he discovered a letter from his sister to his wife that mentioned the gold market, he realized he was being conned. He ordered the Treasury to immediately release large amounts of gold from the reserves.

Black Gold

Initially, it was announced that $4 million worth of gold reserves would be sold. But the government didn't actually have that much. Later, the Treasury Secretary claimed that he meant to say $400,000, but added an extra zero by accident.

On September 24, 1869, later dubbed “Black Friday,” the gold hit the market. Within minutes, the value of gold plummeted. Desperate investors scrambled to sell their holdings and many, including Abel Corbin, were ruined. The fall in gold prices led to a huge dip in the market, which then rippled its ill effects into the national economy.

There was a congressional investigation into the scandal, and Butterfield resigned. Although Grant was not involved, his personal association with Gould and Fisk tainted his reputation.

As for Gould and Fisk, they managed to sell their gold before the bottom dropped out. Gould continued his financial power plays, eventually gaining control of the Union Pacific Railroad and Western Union Telegraph Company. Fisk was shot and killed by a fellow financier a few years later, after an argument over the affections of a Broadway showgirl.

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iStock // Ekaterina Minaeva
technology
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
Original image
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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iStock
Animals
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Scientists Think They Know How Whales Got So Big
May 24, 2017
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iStock

It can be difficult to understand how enormous the blue whale—the largest animal to ever exist—really is. The mammal can measure up to 105 feet long, have a tongue that can weigh as much as an elephant, and have a massive, golf cart–sized heart powering a 200-ton frame. But while the blue whale might currently be the Andre the Giant of the sea, it wasn’t always so imposing.

For the majority of the 30 million years that baleen whales (the blue whale is one) have occupied the Earth, the mammals usually topped off at roughly 30 feet in length. It wasn’t until about 3 million years ago that the clade of whales experienced an evolutionary growth spurt, tripling in size. And scientists haven’t had any concrete idea why, Wired reports.

A study published in the journal Proceedings of the Royal Society B might help change that. Researchers examined fossil records and studied phylogenetic models (evolutionary relationships) among baleen whales, and found some evidence that climate change may have been the catalyst for turning the large animals into behemoths.

As the ice ages wore on and oceans were receiving nutrient-rich runoff, the whales encountered an increasing number of krill—the small, shrimp-like creatures that provided a food source—resulting from upwelling waters. The more they ate, the more they grew, and their bodies adapted over time. Their mouths grew larger and their fat stores increased, helping them to fuel longer migrations to additional food-enriched areas. Today blue whales eat up to four tons of krill every day.

If climate change set the ancestors of the blue whale on the path to its enormous size today, the study invites the question of what it might do to them in the future. Changes in ocean currents or temperature could alter the amount of available nutrients to whales, cutting off their food supply. With demand for whale oil in the 1900s having already dented their numbers, scientists are hoping that further shifts in their oceanic ecosystem won’t relegate them to history.

[h/t Wired]

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