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scenepast

12 Postcard Locations, Then and Now

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scenepast

The images on your postcards might get a little faded over time, but unless you attended Hogwarts, they generally don't change. The real life inspiration is not so inert. Businesses and buildings change so much that you might not recognize some of the locations from your postcards. SCENEPAST, the app that lets you look at famous movie locations over the years, has come up with a new app to let you compare postcards to modern day. ScenePast: Americana Road Trip is a free app that offers a virtual roadtrip through all 50 states. 

Users can explore a variety of nostalgic tourist attractions and discover how time has aged them. It's amazing how some locations are completely different, while others have stood the test of time. 

1. Beverly Hills Holiday Inn (1960s Postcard)

Location: Wilshire Boulevard & North Crescent Drive, Beverly Hills, CA

The Holiday Inn is now a Hotel Sixty, and the building has lost its retro red stripe. It's unclear what used to reside underneath, but presently, it's an art deco-inspired restaurant called Caulfield's.

2. Old South Meeting House (1900s Postcard)

Location: 310 Washington St, Boston, MA
Fun fact: This is where the Boston Tea Party first gathered in 1773

The Old South Meeting House is best known as the church where the conspirators of the Boston Tea Party first met in 1773. Today, the church is ivy-free and surrounded by chain clothing stores.

3. Brown Derby Beverly Hills (1940s Postcard)

Location: 9537 Wilshire Boulevard, Beverly Hills, CA

The Brown Derby is gone, but the Louis Vuitton building gives a subtle nod to the past with its brown, hat-like dome. 

4. Disneyland Hotel Entrance (1960s Postcard)

Location: 1538 Disneyland Drive, Anaheim, CA

The monorail is still present, but as a result of reorganization, the Disney sign has been taken down. The area is now a lot less whimsical.

5. Coney Island Cyclone (1940s Postcard)

Location: 1000 Surf Avenue, Brooklyn, NY

The Cylone is a lot less flashy now. Despite being one of the most famous attractions in Brooklyn, the roller coaster is a no frills ride. 

6. The Miniature Railroad Amusement (1910s Postcard)

Location: Pacific Ave and Windward Ave, Venice, CA

The train is gone, but it's nice to see that a lot of the original architecture is still there. 

7. Quincy Market (1910s Postcard)

Location: 4 South Market, Boston, MA

The Boston market is still up and running, but with considerably fewer carriages. 

8. Fremont Hotel (1960s Postcard)

Location: 200 Fremont Street, Las Vegas, NV

Outside of a new paint job, the Fremont Hotel is almost exactly the same.

9. Disneyland – Tomorrowland (1960s Postcard)

Location: Tomorrowland Way, Anaheim, CA

There's a lot more going on in Tomorrowland these days!

10. Rockefeller Center (1950s Postcard)

Location: 45 Rockefeller Plaza, New York, NY

Not much has changed at Rockefeller Plaza. The iconic pools and flowers are just as lush as ever. 

11. Famous Chef Restaurant (1950s Postcard)

Location: 8315 East Colfax, Denver, CO

A strip club now stands where the Famous Chef Restaurant used to be.  

12. Hotel Apache (1950s Postcard); Binion’s Horseshoe (1970s Postcard); Binion’s Gambling Hall (Today)

Location: 128 Fremont Street, Las Vegas, NV

The building's appearance might change, but the gambling is a constant.

Download the app for free here. 

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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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Name the Author Based on the Character
May 23, 2017
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