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The Last of the (New) New Einsteins

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For the current issue of mental_floss magazine, Erik Vance profiled nine "New Einsteins" "“ visionaries who are discovering how to grow organs, peer into black holes, levitate food, cure plagues, and let blind men see. All week, Mr. Vance has been anointing additional New Einsteins here on mentalfloss.com. The final (new) New Einstein? A dog genius.


Who He/She Is: An unnamed doberman-border collie mix from Southern England


What He/She Did: No one knows the name of the first dog to sniff out a cancerous tumor. Since it was about 90 dog years ago, the clever pup has probably gone to the great fire hydrant in the sky by now. But the story was documented by Hywel Williams and Andres Pembroke in the British journal, Lancet, in 1989. Apparently the unnamed canine became obsessed with a mole on the leg of its owner "“ sniffing at it constantly, even when it was covered by clothes. Eventually, the dog got tired of having its prognosis ignored and simply decided to remove the mole with an ad hoc surgery involving its teeth.


When the owner finally went to Williams and Pembroke, she found out that the mole was cancerous and that the dog had probably saved her life.

Why You Should Start Idolizing Him/Her Immediately:

First of all, after succeeding where billions of dollars in federal funding have come up short, this creature likely went home and licked its own privates. That's got to be impressive in anyone's book.

Second of all, the discovery led to a whole new way to think about cancer detection. Scientists knew that tumors release all manner of exotic trace chemicals like alkanes and that they could theoretically be detected, say, on your breath if you looked carefully. But it never occurred to anyone that they might stink.

The notion that cancer has an odor has led scientists to start examining the some 3,000 chemicals that leave the body every day. Recently, scientists have confirmed that certain skin cancers can be detected in the air just above the tumor using devices called gas chromatography mass spectrometers. The analysis takes a day or two.

But when it comes analytic chemistry, the best in modern technology can just barely compete with the human nose, which can detect some of the more noxious chemicals in the parts per quadrillion (think a pinhead drop of liquid in a container the size of the Astrodome). Now consider that dogs can smell chemicals with at least 1,000 times that sensitivity.

Which brings us back to the Doberman mix. Today, dogs have detected nascent lung cancer and breast cancer with 88-99 percent sensitivity "“ theoretically more accurate than pap tests and mammograms. This has led to a number of clinics training cancer dogs to look for lung and bladder cancer. When you think about it, it's not all that different from the way we used to test for pregnancy by injecting frogs with women's urine.

So next time you go for a check up, don't be surprised if your clinician greets you by humping your leg.

Previous (New) New Einsteins: Marin Soljačić , Roland Fryer, Nathalie Cabrol, David Shaw

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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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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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