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Neural Network Trained to Spot Spoilers

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Researchers after my own heart have developed an AI-based system that can flag spoilers in online reviews of books and TV shows.

A team from the University of California San Diego will present their findings at the upcoming Association for Computational Linguistics annual meeting in Italy.

“Spoilers are everywhere on the Internet, and are very common on social media,” senior study author Ndapa Nakashole, computer science professor at UC San Diego, said in a statement. “As Internet users, we understand the pain of spoilers, and how they can ruin one’s experience.”

Amen!

Some reviewers are kind enough to splash a spoiler-alert warning across their articles, before too much is revealed. But not everyone understands the crushing disappointment of prematurely knowing important plot details.

The folks at UCSD do, though. So they invented SpoilerNet—a neural network that automatically detects spoilers.

To train and test their system, the team collected more than 1.3 million book reviews annotated with spoiler tags from Amazon-owned social cataloging site Goodreads.

SpoilerNet has a knack for spotting literary leaks, performing at an impressive rate of 89 to 92 percent accuracy.

It did struggle, however, with a dataset of more than 16,000 single-sentence summaries of about 880 TV shows, detecting spoilers with only 74 to 80 percent accuracy.

Most of the errors, according to UC San Diego, came from the system getting distracted by words—like “murder” or “killed”—that are usually loaded and revelatory.

“To our knowledge, this is the first dataset with spoiler annotations at this scale and at such a fine-grained granularity,” PhD student and first author Mengting Wan said.

Spoilers date back to the early days of the Internet, when online etiquette insisted they could and should be avoided—or at least marked by an obvious warning.

But caution is often thrown to the wind, and many unwitting readers have had literature, films, and television programs “spoiled.”

UC San Diego’s project is deeper than simply saving people from the threat of unwanted information. Researchers aim to better understand how people write spoilers, and what kind of linguistic patterns and common knowledge mark a sentence as such.

Spoiler alert: Different users have different standards for tagging content; what’s important to one may be mundane to another. And that’s going to make calibrating a neural network quite challenging.

Moving forward, the researchers expect their dataset could be used to train algorithms to detect spoilers on different platforms.

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FaceApp Responds to (Mostly Unfounded) Privacy Concerns

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Appearance-altering platform FaceApp has, once again, come under fire—this time from privacy advocates.

The AI-powered selfie editor from Russian company Wireless Lab uses neural network technology to generate highly realistic transformation of faces in photographs.

Launched in early 2017, FaceApp almost immediately faced criticism over its “ethnicity filters” and, later, the “hot” transformation feature that reportedly lightened skin color.

Both options have since been removed.

Curious about what you’d look like with a different hair or eye color? Want to virtually test out bangs before making the cut? Wonder what you’d look like as a Hollywood star or someone of the opposite gender?

The face-morphing app does it all.

It even bends time to reveal what you might look like in the future.

“Through we might not be able to influence your wisdom, we can certainly add some wrinkles to your face,” the FaceApp website said.

The new “time travel” filter has garnered attention around the world: Check out what the Jonas Brothers, Terry Crews, Sam Smith, Drake, and Zachary Levi look like as old fogies.

With great virality comes great responsibility, though. And some believe FaceApp isn’t taking that responsibility seriously.

Concerns have been raised about whether the application uploads users’ camera roll in the background (of which there is seemingly no evidence), and how it allows you to pick photos without allowing access.

“We are receiving a lot of inquiries regarding our privacy policy and therefore, would like to provide a few points that explain the basics,” the Russian startup told TechCrunch.

For starters, FaceApp performs “most” of its photo processing in the cloud (Amazon Web Services and Google Cloud, specifically), uploading only those pictures selected by a user.

“We never transfer any other images from the phone to the cloud,” the statement said. “Most images are deleted from our servers within 48 hours from the upload date.”

FaceApp also claims that no user data is “transferred to Russia,” where its core R&D team is located.

“We don’t have access to any data that could identify a person [and] we don’t sell or share any user data with any third parties,” it added.

But that’s not enough for some U.S. policymakers.

Sen. Chuck Schumer (D-NY) has asked the FBI and FTC to look into FaceApp’s data handling practices.

“I have serious concerns regarding both the protection of the data that is being aggregated as well as whether users are aware of who may have access to it,” Schumer wrote in a letter to the government agencies.

“In the age of facial recognition technology as both a surveillance and security use,” he continued, “it is essential that users have the information they need to ensure their personal and biometric data remains secure, including from hostile foreign nations.”

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Ford Secretly Designed a Pickup Truck Emoji (And It’s Been Shortlisted By Unicode)

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There are at least 10 different emojis to represent trains, but none that denote a pickup truck.

Ford Motor Company wants to change that.

“When customers started demanding a truck emoji, we knew we had to help make it happen,” Joe Hinrichs, president of Ford automotive, said in a statement. “Given the popularity of Ford trucks globally, there’s no one better than Ford to help bring an all-new pickup truck emoji to hard-working texters around the globe.”

Last year, the automaker submitted a proposal to the Unicode Consortium—judge, jury, and executioner of new emoji—to add a truck icon to keyboards.

The character—a simple blue pickup—has since been short-listed for inclusion in a future version of Unicode.

“Our team spent a lot of time digging through message boards, texting influencers, and watching social media feeds to really understand our customers’ needs,” according to Craig Metros, Ford North America design director.

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“People want a truck emoji that’s fresh, stylish, carries their ideas, and ‘tows’ the line on what a truck means,” he said. “The end result is a modern icon that should give all truck fans a smiley face emoji.”

Ford is no stranger to “innovations”: This is the same company, remember, that brought you a noise-cancelling kennel, lane-keeping bed, and self-braking trolley. (All, unfortunately, still in the prototype stage.)

Now, following months of top-secret development and testing, the company is making waves again with its new pickup truck emoji.

If approved, the design will be customized for all mobile platforms and could start driving onto digital screens as early as next year.

In the meantime, iOS and Android users can look forward to a slew of new food, animal, activity, and smiley face characters—including more diverse and inclusive icons—set to hit keyboards this fall.

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Toyota’s Electric Vehicle Will Transport 2020 Olympic Athletes, Visitors

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Toyota is developing an Accessible People Mover (APM) to ferry folks around the 2020 Summer Olympics.

Designed for use at next year’s Olympic and Paralympic Games, the APM offers a “last one mile” solution, transporting as many individuals as possible to competitions and venues.

Athletes, staff, and visitors with accessibility needs (think elderly, handicapped, pregnant, as well as families accompanied by small children) will have access to some 200 APMs in Japan’s capital city.

Their primary intention, project lead Akihiro Yanaka told The Japan Times, is to transfer people around Olympic settings: APMs could, for instance, carry someone from a stadium entrance to the gate nearest their seat.

The Accessible People Mover, which looks like a giant golf cart, is a low-speed, short-distance battery electric vehicle (BEV), capable of carrying six bodies— passengers and one driver—on three rows of seats.

It is also equipped with a ramp and can accommodate one wheelchair at a time by folding away the second-row seat.

The APM is a low-speed, short-distance battery electric vehicle suitable for carrying visitors and athletes at the Olympic and Paralympic Games (via Toyota)

An open concept means riders can enter and exit from either side, using built-in safety bars; the van is also equipped with rain curtains, according to the Times.

Powered by lithium-ion batteries, Toyota’s taxis can travel 100 km (62 miles) on a single charge, at a maximum speed of 19 kph (12 mph), chauffeuring people to various facilities, including non-event sites like the Olympic Village.

One part of the fleet may be earmarked for relief activities (i.e. a non-emergency ambulance), considering the vehicles are large enough to fit a stretcher and at least two staffers, plus the driver.

The automaker plans to test the squadron and make further improvements ahead of the 2020 Games.

A major sponsor of next summer’s sporting extravaganza, Toyota is also contributing a handful of Human Support Robots (HSR) and Delivery Support Robots (DSR), which will roam the National Stadium, carrying food and other goods, guiding people to their seats, and providing event information.

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