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15 Facts About Fast Times at Ridgemont High

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Even if you already have most of Fast Times at Ridgemont High memorized, get to know the teen sex comedy on a deeper level with these behind-the-scenes facts.

1. Fast Times at Ridgemont High began as a non-fiction book.

While a freelance writer for Rolling Stone, screenwriter Cameron Crowe spent a year secretly embedded at Clairemont High School in San Diego, California under an assumed name (and in cooperation with the school’s administration) to gather stories for a non-fiction book with the same title. Crowe’s book was published in 1981; a year later, it was adapted for the screen.

2. The inspiration for Mark “The Rat” Ratner would go on to become a real-life computer guru.

Crowe based the geeky Rat on then-Clairemont High School student Andy Rathbone. Rathbone eventually became rich and famous for writing many of the “…for Dummies” books about computer programs like Windows.

3. Fast Times is Amy Heckerling’s directorial debut.

Heckerling, who would go on to direct Look Who’s Talking and Clueless, was hired to direct Fast Times at Ridgemont High based on her AFI thesis film. Called Getting it Over With, it’s about a 19-year-old girl trying to lose her virginity before she turns 20.

4. Jennifer Jason Leigh also did a bit of undercover work to prepare.

Twenty-year-old Leigh took a job at the actual Perry’s Pizza in the Sherman Oaks Galleria mall, where parts of the movie were shot, to get into character as Stacy Hamilton.

5. Nicolas Cage made his big screen debut in Fast Times as “Brad’s Bud.”

Cage was originally supposed to play Brad, but the filmmakers relegated him to a background role after his improvisations during the auditioning process were deemed too weird. The credits list Cage as “Nicolas Coppola.” He later changed his last name professionally to avoid charges of nepotism—he is the nephew of director Francis Ford Coppola.

6. Despite being a movie about high school, Cage was the only cast member under the age of 18.

Because of the sometimes-explicit nature of the film’s subject matter, casting directors made sure actors who auditioned were 18 years of age or older. Cage, who was only 17, lied about his age to snag a role.

7. Sean Penn didn’t have to audition for the Spicoli role.

He was cast after a brief chat prior to his scheduled audition.

8. Penn stayed in character during the film’s entire shoot.

Always the method actor, Penn forced everyone on-set to call him “Spicoli” and wouldn’t answer to his actual name. Other Fast Times actors made fun of him behind his back by calling him “Sean DeNiro.”

9. Fast Times is Best Actor Oscar-winner Forest Whitaker’s first film.

He plays enraged football player Charles Jefferson.

10. Herman Munster thought the movie was too obscene.

Fred Gwynne (Herman Munster from the television show The Munsters) was originally offered the role of Mr. Hand, but he turned it down because he objected to the teenage sex and drug use in the script.

11. Universal Studios originally approached David Lynch to direct.

He politely turned them down, saying the script wasn’t in his wheelhouse.

12. Bruce Springsteen’s sister has a cameo.

She plays the dark-haired cheerleader on the left during the pep rally.

13. No original music was written for the film.

The score was taken from Universal Studios’ library of prerecorded music.

14. Heckerling and Crowe filled the cast with friends and lovers.

Judge Reinhold was asked to play Brad because he was director Amy Heckerling’s upstairs neighbor in Los Angeles. Heckerling also cast her ex-husband, David Brandt, and his real-life band, Reeves Nevo & The Cinch, as the band at the dance and her ex-boyfriend, Beverly Hills Cop and Scent of a Woman director Martin Brest, as the doctor on the field trip near the end of the film. The woman who pulls up next to Brad’s car and laughs at him while he’s wearing his Captain Hook’s Fish and Chips uniform is Crowe’s then-girlfriend and ex-wife Nancy Wilson, guitarist for the band Heart.

15. Heckerling originally wanted to keep the fate of each character open-ended.

But Universal Studios mandated she end the movie with updates for each character, just like 1973’s American Graffiti.

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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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