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How Merrill, Goldman and the Brothers Lehman made their Money

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The Dow took a nosedive yesterday. Colbert called it "Watership Dow." Drudge referred to it as a "Nightmare on Wall Street." And while I'm not sure whether to smile or grimace at the headlines (I have to commit to one, so I don't look A.D.D. about being bipolar), the news did give me reason to look up some corporate histories. Here's some dirt I pulled straight from Wikipedia. And unless this jokester's been messing with the entries, I'm guessing they're accurate.

Merrill Lynch

There's no doubt that Charles Merrill was a genius. Not only did the Amherst and Michigan Law alum foresee the Great Depression (he divested many of his holdings before the crash), he also begged Calvin Coolidge- a fellow Amherst alum- to speak out against the stock market speculation. The Merrill Lynch group, which went through numerous name and line-up changes (Charles E. Merrill & Co., Merrill, Lynch & Co., Merrill Lynch, E. A. Pierce, and Cassatt, Merrill Lynch, Pierce, Fenner & Beane) made some of their first big money by investing in what would become RKO Pictures (in 1921), and in purchasing a controlling share of Safeway grocery stores in 1926.

Goldman Sachs

Picture 8.pngA week ago, I would have thought Goldman Sachs was the gold standard in investment banking, but apparently, that hasn't always been the case. In fact, they got into quite a bit of trouble in the late 1920's. Founded in 1869 by Marcus Goldman, a Jewish immigrant from Germany, the company started off in the paper business. When Goldman's son-in-law joined the company it added the Sachs to the banner, and the company made it's first big money when it got into the Initial Public Offering game. They managed the Sears, Roebuck and Company IPO in 1906, the biggest to date. Apparently, things were humming for a while. They hired a ton of MBA's (giving more credence to the degree). Unfortunately, they severely marred their reputation when they offered a "closed end fund" to investors. It ended up working much like a Ponzi scheme, and the whole thing came to a head in the big stock market crash of '29. According to Wikipedia, it took years to fix the damage to the brand. In fact, it wasn't until 1956, when they managed the Ford Motor Company's IPO that they earned their reputation back.

AIG

Picture 10.pngWho knew that AIG started out in Shanghai? The company was the brainchild of Cornelius Vander Starr, a clever American who became the first Westerner to offer insurance to the Chinese. Wikipedia lists him as the son of a Dutch railroad engineer who started an ice cream business at 19, moved to California and sold car insurance while studying for the bar the next year, then took a job as a clerk for the Pacific Mail Steamship company where he (maybe) sorted mail and (definitely) found himself in Japan. In any case, he started AIG in 1919, sold insurance to other foreign markets once he'd established himself in Asia, and moved the company to New York City after the Communist Party took over in 1949.

Lehman Brothers

Picture 9.pngPerhaps the strangest of the origins to me was that of Lehman Brothers. I'd always just assumed that the (formerly) prestigious firm was a New York institution, and had been started by Yankee elites in the last 60 or 70 years. Apparently, the story begins in Montgomery, Alabama! The 20-something Henry Lehman moved to southern state straight from Bavaria, and set up a dry-goods store. Slowly, Lehman's two brothers moved to the states, and joined him, and together they started realizing the value of cotton. They even began to accept cotton as payment in their store. When Henry passed away from Yellow Fever in 1855, the remaining brothers Lehman moved their operations to New York, where they continued to capitalize on the cotton market, teamed up with Goldman on his Sears IPO deal, and underwrote hundreds of gigantic IPO's- from Macy's to Woolworth's to Studebaker's to B.F. Goodrich's. Clearly, it's been an institution for for quite a while. The company stopped being a family-only firm in 1924, and they survived the Great Depression by making smart venture capital investments.

Special thanks to Bill Pearson for sparking the interest!

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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
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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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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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