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Early Bird Gets the Internet Worm

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When Robert Tappan Morris was a graduate student at Cornell in 1988, he had a clever idea: he would release a self-replicating program (or "worm") onto the Internet, reportedly in an effort to highlight security problems in computer networks. Morris's worm exploited vulnerabilities in common computer systems, allowing it to propagate at will onto new computers via the Internet. The worm was designed to use minimal computer resources, but in the wild its effect proved to be devastating.

Morris released his worm on November 2, 1988 (twenty years ago yesterday), directing instances of the program to report back to a host computer so that he could monitor its spread. The epidemic spread faster than Morris had expected, aggressively infecting and reinfecting computers around the U.S. Infected computers became overloaded and unresponsive, causing system administrators to panic. Within hours of its release, the worm had infected thousands of computers, and wasn't nearly as well-behaved as Morris had hoped. When Morris realized what was happening, he and a Harvard friend emailed information that would help stop the worm -- but it was too late, as email routes were already clogged...by Morris's worm.

System administrators and computer scientists banded together to fight the worm, disassembling the program and locking down its modes of transmission. Others disconnected their systems from the Internet to avoid becoming infected. Within two days the worm was largely eradicated, but Morris's troubles were just beginning: he was eventually indicted under the Computer Fraud and Abuse Act of 1986, and the U.S. General Accounting Office issued a report on the worm -- Morris had succeeded in focusing attention on computer security after all. (The report actually begins with the text: "This is the first GAO report to be made available over the Internet. GAO wants to know how many people acquire the report this way. If you are reading this, please send mail to me swolff@nsf.gov and I'll keep count for them. Your name will not be saved or used." I have to wonder how many emails swolff@nsf.gov has gotten about the report over twenty years!) Pictured at left: the source code of Morris's worm, on display (in binary form on a 3.5" floppy) at The Computer History Museum.

Morris was sentenced to three years of probation, 400 hours of community service, a $10,050 fine, and the costs of his supervision. Nearly twenty years after the worm was released, Morris is now a tenured professor at MIT; his MIT homepage makes no mention of the worm.

To read more on the worm and its aftermath, check out a contemporaneous report by Bob Page written on November 7, 1988. Network World also posted a nice retrospective of the worm last week. RTM's worm was also discussed at length in the classic Cyberpunk by Hafner and Markoff.

(Worm source code photo courtesy of Flickr user Go Card USA.)

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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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Nick Briggs/Comic Relief
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What Happened to Jamie and Aurelia From Love Actually?
May 26, 2017
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Nick Briggs/Comic Relief

Fans of the romantic-comedy Love Actually recently got a bonus reunion in the form of Red Nose Day Actually, a short charity special that gave audiences a peek at where their favorite characters ended up almost 15 years later.

One of the most improbable pairings from the original film was between Jamie (Colin Firth) and Aurelia (Lúcia Moniz), who fell in love despite almost no shared vocabulary. Jamie is English, and Aurelia is Portuguese, and they know just enough of each other’s native tongues for Jamie to propose and Aurelia to accept.

A decade and a half on, they have both improved their knowledge of each other’s languages—if not perfectly, in Jamie’s case. But apparently, their love is much stronger than his grasp on Portuguese grammar, because they’ve got three bilingual kids and another on the way. (And still enjoy having important romantic moments in the car.)

In 2015, Love Actually script editor Emma Freud revealed via Twitter what happened between Karen and Harry (Emma Thompson and Alan Rickman, who passed away last year). Most of the other couples get happy endings in the short—even if Hugh Grant's character hasn't gotten any better at dancing.

[h/t TV Guide]

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