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Conrad on the left (via NASA)

The Astronaut Whose First Words on the Moon Were a Joke

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Conrad on the left (via NASA)

If Apollo 12's crew were nervous, they certainly didn't let it show. Commander Pete Conrad and Lunar Module Pilot Alan Bean spent a pretty good chunk of their seven and a half cumulative hours on the lunar surface cracking jokes and having a good time. Here's a typical excerpt from their mission transcript:

Conrad: Okay, very good. "(Photograph) contingency sample area" I got. "Deploy the color chart (on an undisturbed surface)" Ho ho. Take your time, Al. (Pause) Hey, I'm learning to do it. (Pause)

Bean: (Pete belches) Houston, how does the LM look? I'm getting ready to go out the front door.

Conrad: Dum dee dum dum. (Pause) Whoops. No way I'm gonna...I wonder if I can get in the bottom of this crater hole?
...
Conrad: Dee dum dee dum. I feel like Bugs Bunny. (Pause; Giggles) (Pause)

Perhaps this is because they knew they wouldn't sink into the moon's unknown, powdery surface like quicksand, which was a real concern raised by astrophysicist and NASA consultant Dr. Tommy Gold leading up to the Apollo 11 mission. He based this theory on radio observations of the moon and passed it along to anyone who would listen, including Neil Armstrong and Buzz Aldrin.

Gold was widely mocked, but this thought was no doubt lingering in the back of the astronauts' minds as their lunar module touched down. The craft didn't disappear into the moon's surface, of course, and Armstrong was able to take his famous first step and utter those immortal words, "That's one small step for a man, one giant leap for mankind." (Armstrong insists he included "a," although it was dropped from recordings in transmission.) This downright profound statement—which he says was not planned—put the entire enterprise into focus. It also worked as a setup for Pete Conrad's first words on the moon, which, naturally, were a joke.

Pete Conrad was a Princeton educated aeronautical engineer, Navy test pilot, and all-around character. Leading up to the mission, Oriana Fallaci, an Italian journalist, said she thought the government told the astronauts what to say while on the moon. To prove this wasn't the case, Conrad told her exactly what he was going to say—and bet her five hundred bucks to prove that he was going to say it.

So when Conrad stepped from the lunar module and onto the pad to become the third man ever to walk on the moon, he made good on his promise and said those first words: "Whoopie! Man, that may have been a small one for Neil, but that's a long one for me."

Conrad was only 5'6", so his wager-winning statement also proved to be the first bit of extraterrestrial self-deprecation in human history. (A detailed account of the bet is featured in Andrew Chaikin's A Man on the Moon.)

According to Conrad, he never got paid that $500. Something tells us the story's worth far more than that.

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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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May 23, 2017
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