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What Happens to Leftover Campaign Funds When a Candidate Drops Out?

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After disappointing performances in the Iowa and New Hampshire Caucuses, Republican presidential candidates Chris Christie and Carly Fiorina have already called off their campaigns. This weekend, former Florida governor Jeb Bush also decided to bow out. But what happens to all the leftover campaign funds—Bush had raised more than $150 million, the most of any GOP candidate—when the low-polling candidates drop out?

One thing's for sure: Upset candidates can't console themselves by putting the dough toward a new yacht and sailing off to recuperate. The Federal Election Commission has strict rules about what federal candidates can and can't do with leftover campaign money, and the biggest directive is that they can't pocket it for personal use.

Here's what a campaign committee is allowed to do with any lingering cash: it can donate the funds to charities or political parties; it can contribute $2000 per election to other candidates; and it can save the money in case the candidate chooses to run again. However, those regulations don't apply to the relatively new super PACs (Political Action Committees); this is only the second election where they have played a role, and there are currently no rules to stipulate what happens to that money beyond that it cannot go to fund another federal candidate. Much of that money tends to be returned to its original donors, used to wrap up the failed campaign, or donated to back a state-level candidate. The goal, however, is always to spend all of that money.

Running a campaign is an expensive proposition—Barack Obama spent nearly $750 million on his 2008 White House bid, and in 2012 he spent $985 million on reelection while challenger Mitt Romney spent $992 million—and insufficient cash is often a reason campaigns go belly up.

As for winning (or sometimes losing) politicians, they'll often put their leftover funds toward their next race. If they choose not to run, they have to abide by the same FEC rules. Wonder why this law is in effect? Until 1993, U.S. Representatives who took office before January 8, 1980, were allowed to keep any leftover campaign cash when they retired, but a study showed that a third of Congress kept and spent millions in campaign donations on personal items like clothing, jewelry, artwork, personal travel, and dry cleaning. Embarrassed, Congress passed a law negating this custom for the House; the Senate already had provisions in place so this wouldn't happen.

In reality though, officials can usually find a way to make that cash still work for them (and state laws differ from federal ones). After Christie won reelection as New Jersey's governor in 2014, his campaign was granted permission to use some of its remaining war chest to cover the legal fees Christie incurred during the Bridgegate scandal. And this was well before he dropped $26.7 million on his failed presidential bid.

A version of this article originally ran in 2012.

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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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Scientists Think They Know How Whales Got So Big
May 24, 2017
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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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