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Ken Jennings: Watson “has never known the touch of a woman.”

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Above: Watson as “Turd Ferguson.”

In the days since IBM’s Watson defeated Ken Jennings and Brad Rutter on Jeopardy!, Jennings has written several articles about his experience — they’re funny, personal, and a bit technical. In other words, required reading. Here’s a roundup.

My Puny Human Brain

In this Slate article, Jennings discusses his matches against Watson, and what it’s like to play in a humans-versus-machines grudge match. Here’s a snippet:

Indeed, playing against Watson turned out to be a lot like any other Jeopardy! game, though out of the corner of my eye I could see that the middle player had a plasma screen for a face. Watson has lots in common with a top-ranked human Jeopardy! player: It’s very smart, very fast, speaks in an uneven monotone, and has never known the touch of a woman. But unlike us, Watson cannot be intimidated. It never gets cocky or discouraged. It plays its game coldly, implacably, always offering a perfectly timed buzz when it’s confident about an answer. Jeopardy! devotees know that buzzer skill is crucial—games between humans are more often won by the fastest thumb than the fastest brain. This advantage is only magnified when one of the “thumbs” is an electromagnetic solenoid trigged by a microsecond-precise jolt of current. I knew it would take some lucky breaks to keep up with the computer, since it couldn’t be beaten on speed.

Read the rest for some more insight, including the crucial capture of most Daily Doubles by Watson: “Game over for humanity.”

Ken Jennings Op-Ed: ‘Jeopardy!’ champ says computer nemesis Watson had unfair advantages

In this New York Daily News piece, Jennings writes about the Buzzer Problem, as discussed in a previous mental_floss blog post. Here’s what Jennings wrote:

The key to Watson’s dominance lies in the famously tricky Jeopardy! buzzer, the signaling device that allows players to respond to the show’s clues. Like any human player, Watson does buzz with a “thumb” of sorts (actually a magnetic coil mounted over a buzzer), but it can also rely on the millisecond-precision timing of a computer. The reflexes of even a very good human player will vary slightly, but not Watson’s. If it knows the answer, it makes the perfect buzz. Every single time. And it’s hard to win if you can’t buzz. Imagine if John Henry had to beat the steam engine at a feat of brute strength just to be allowed to swing his hammer, or if chess grandmaster Garry Kasparov had to solve a long-division problem faster than supercomputer Deep Blue every time he moved a piece in their epic match.

Read the rest for some more analysis, including the “split the losings” issue — playing one computer against two humans, so the humans’ totals would be split.

Statistical Analysis of Jeopardy! Categories and Clues

In this Slate article (boy, Slate’s really tearing it up on the Jeopardy! coverage lately!), Jeremy Singer-Vine runs the numbers on the most common categories and the hardest clues on the show, as well as where the Daily Doubles lurk. Here’s a tidbit:

Knowing what categories show up most frequently might be helpful in preparing for an appearance on the show. But let’s get down to the clue level: What’s the most common answer on Jeopardy? That would be “What is Australia?” That response appears in J-Archive 208 times, out of 197,736 total answers—to clues as diverse as “In terms of rainfall, it’s the driest continent after Antarctica” and “The overarm ‘crawl’ swimming stroke was introduced to England in 1902 from this country.” (For technical reasons, I’m only counting the first two rounds of Jeopardy in this analysis. Also note that while Google Refine helped group answers like “Burma (Myanmar)” and “Myanmar (or Burma),” idiosyncrasies among transcribers means that the answer-counts are inevitably imprecise.) In fact, thanks to the prominence of geography-related categories, the Top 23 answers are all places. (Click here for a list.) At No. 24: George Washington.

(Photo of Watson as “Turd Ferguson” courtesy of charliecurve, used under Creative Commons license.)

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technology
Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
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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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Health
One Bite From This Tick Can Make You Allergic to Meat
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iStock

We like to believe that there’s no such thing as a bad organism, that every creature must have its place in the world. But ticks are really making that difficult. As if Lyme disease wasn't bad enough, scientists say some ticks carry a pathogen that causes a sudden and dangerous allergy to meat. Yes, meat.

The Lone Star tick (Amblyomma americanum) mostly looks like your average tick, with a tiny head and a big fat behind, except the adult female has a Texas-shaped spot on its back—thus the name.

Unlike other American ticks, the Lone Star feeds on humans at every stage of its life cycle. Even the larvae want our blood. You can’t get Lyme disease from the Lone Star tick, but you can get something even more mysterious: the inability to safely consume a bacon cheeseburger.

"The weird thing about [this reaction] is it can occur within three to 10 or 12 hours, so patients have no idea what prompted their allergic reactions," allergist Ronald Saff, of the Florida State University College of Medicine, told Business Insider.

What prompted them was STARI, or southern tick-associated rash illness. People with STARI may develop a circular rash like the one commonly seen in Lyme disease. They may feel achy, fatigued, and fevered. And their next meal could make them very, very sick.

Saff now sees at least one patient per week with STARI and a sensitivity to galactose-alpha-1, 3-galactose—more commonly known as alpha-gal—a sugar molecule found in mammal tissue like pork, beef, and lamb. Several hours after eating, patients’ immune systems overreact to alpha-gal, with symptoms ranging from an itchy rash to throat swelling.

Even worse, the more times a person is bitten, the more likely it becomes that they will develop this dangerous allergy.

The tick’s range currently covers the southern, eastern, and south-central U.S., but even that is changing. "We expect with warming temperatures, the tick is going to slowly make its way northward and westward and cause more problems than they're already causing," Saff said. We've already seen that occur with the deer ticks that cause Lyme disease, and 2017 is projected to be an especially bad year.

There’s so much we don’t understand about alpha-gal sensitivity. Scientists don’t know why it happens, how to treat it, or if it's permanent. All they can do is advise us to be vigilant and follow basic tick-avoidance practices.

[h/t Business Insider]

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