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The Late Movies: Science Shows for Kids

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After the smashing success of the Mr. Wizard edition of the Late Movies, we thought we'd give you more childhood science shows. Here are some of our favorites. But if we left your preferred educational programming off this list, tell us in the comments!

Beakman's World

Original run: 1992"“1998
Original channel: Beakman's world premiered on TLC, but after a year, was picked up by CBS.
Fun fact: The Beakman's World theme song was composed by Mark Mothersbaugh of Devo.

Watch Mr. Wizard

Original run: 1951"“1972
Original channel: NBC
Fun fact: Before achieving television fame, Don Herbert (Mr. Wizard) acted opposite Nancy Davis Reagan at Couch House Summer Theater in 1940.

Mr. Wizard's World

Original run: 1983"“1990
Original channel: Nickelodeon
Fun fact: In 1942, Don Herbert worked as a guide at Rockefeller Center.

The Magic School Bus

Original run: September 10, 1994"“December 6, 1997
Original channel: PBS, Fox Kids, Discovery Kids
Fun fact: Ms. Frizzle was voiced by famed actress Lily Tomlin, who was awarded a Daytime Emmy for the role.

The Science Lab of Grand Hank

Original run: 1997-present
Original channel: PSTV (The School District of Philadelphia cable-access channel)
Fun fact: Tyraine Ragsdale dubbed himself "Grand Master Hank" while DJing at the University of Pittsburgh and later used a version of that nickname for his science education career.

Bill Nye the Science Guy

Original run: September 10, 1993"“February 20, 1998
Original channel: PBS
Fun fact: From 2000 to 2002, Nye was the technical expert in BattleBots, the popular combat robot show.

Newton's Apple

Original run: 1983"“1998
Original channel: PBS
Fun fact: For most of the run, the show's theme song was "Ruckzuck" by Kraftwerk.

The Dr. Fad Show

Original run: 1988-1994
Original channel:
Fun fact:
Ken Hakuta (Dr. Fad) invented the Wacky Wall Walker, a very popular toy in the 1980s.


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iStock // Ekaterina Minaeva
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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Name the Author Based on the Character
May 23, 2017
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