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5 Fictional Companies Owned by Microsoft

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Microsoft runs an entire corporate empire you might not know about, but are probably hosting somewhere on your computer. They are the companies of Access and SharePoint, of Excel and SQL Server, and comprise all of that sample data included to give you some idea of how the software works.

1. Contoso

According to Businessweek, Sony has a financial services division that mostly sells life insurance policies. This division is worth more than the rest of the company combined. As one analyst put it, “Sony is a life insurance company with a money-losing TV business.”

Clearly, then, a company like Contoso Ltd. is not without precedent. There’s Contoso Bank, with divisions in the United States and Australia, and an arm in Singapore called Asean Bank. Contoso Pharmaceuticals is spread across the United States, with offices in Denver, Chicago (where its IT center is located), Atlantic, Sacramento, and its corporate headquarters in New York City.

The IT department of Contoso Pharmaceuticals alone supports 195,000 users, which suggests a total headcount somewhere in that area, including contractors and interns. (For comparison, Verizon Communications employs a total of 193,900 people; Disney “only” employs 156,000.) It’s hard to estimate how many people fall under the combined corporate empire, but it likely blows United Technologies—which builds both elevators (as Otis) and UH-60 Black Hawk helicopters for the U.S. Army—out of the water.

2. The Volcano Coffee Company

The Volcano Coffee Company is renowned not only for its blends, which continue a legacy “reminiscent” of ancient Mo’a Mana tribal ways, but also for its forward-thinking embrace of technology. Its owners have developed an InterNET Home Page for the World Wide Web. They’ve even accepted sponsorship by way of a rectangular animated Compuserve GIF.

The company’s name derives from a little known botanical fact that coffee plants grow natively only in the volcanic region of South Sea islands. The Volcano Coffee Company wants you to know that the coffee fields “yield the plumpest, most flavor-filled coffee beans in the world.” Coffee mugs are available from the online gift shop for a mere $25, which means 20 years after Volcano set the web standard, nobody’s figured out how to make and sell a cheap mug online.

3. Northwind Traders

GeeksEngine

According to its business plan, the mission of Northwind Traders is “to become the premier provider of adventure vacations for 25- to 35- year-old professionals.” And the company seems to be well on its way. It started as a clothing store employing seven people. (Last year, the retail arm of the company earned profits of $200,400 on sales of $1,419,500.) Today, Northwind employs 200 people, with a goal of adding another 420 employees in its first year as a travel agency, and raising the total to 1400 the following year.

Before fully divesting itself of the clothing store, the company intends to raise $83,500 from outside sources, making it the most efficient company in Seattle. Still, before investing, one really ought to consider the area. Because Northwind is located in a technology hub of the nation, one has to wonder how the company plans to make everyone forget about the Internet and companies with William Shatner as their front man, to say nothing of Margie’s Travel, another Microsoft baby.

(Those of you downloading your business school essays from the Internet should be warned that ABN Traders has a suspiciously similar business plan to Northwind, as does Aussie-One Travel Agency, which in a twist has a partnership with Margie’s Travel.)

4. World Wide Importers

Just as its name suggests, World Wide Importers imports things from around the world. The company specifically focuses on clothing, which is then sold to U.S. retailers. World Wide Importers employs 4500 people, which is just about the same number as Groupon. Really. (I have no idea what those people are doing all day.) World Wide Importers has locations in three cities: Chicago, where marketing, research, and HR operate; Boston, for sales, shipping, and inventory; and Denver, for customer service.

5. Blue Yonder Airlines

Frequent flyers should go ahead and bookmark Blue Yonder Airlines. It is “the leading adventure charter airline in the US!” with “the industry’s best safety record.” More importantly, though, it has an on-time-every-time guarantee, which has to be the worst business decision in the history of enterprise, but the best deal a traveler is ever going to find. There’s no hedging here, either. Their guarantee reads: “If we fail to depart or arrive on time, we will pay for your accommodations.” Before you start eyeing a Skyloft at the MGM Grand, however, you should probably take note that Blue Yonder has a 100 percent on-time record.

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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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Stephen Missal
crime
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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]

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