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iStock

New App Teaches Kids How to Code With Japanese Pocky Candy

iStock
iStock

Japanese snack company Glico wants to make learning to code more appetizing. According to Engadget, the manufacturers behind the beloved Japanese snack Pocky recently launched a new mobile app called Glicode that teaches anyone how to write simple and basic code using candy and cookies.

In order to complete the game, users position and arrange Pocky and other Glico snacks (like Almond Peak and Biscuit Cream Sands) on a white paper towel in a way that translates into computer commands. Afterwards, users take a photo of the combo. If that code is correct, Haguhagu, the feature character, will move through various obstacles to complete the level.

While Glicode is targeted towards children, the app is suitable for anyone who wants to learn how to code. Currently, it’s only available for Android in the Google Play Store in Japan, but Glico is working on an iOS version. Check it out below.

[h/t Engadget]

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Sensorwake, Kickstarter
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Wake Up to the Aroma of Cappuccino With This Scent-Emitting Alarm Clock
Sensorwake, Kickstarter
Sensorwake, Kickstarter

Some people need an aggressive alarm clock to get them out of bed, like Simone Giertz's slapping robot, or the singNshock, which zaps you if you hit the snooze button. For others, a gentler wakeup call is what does the trick. That's what you get with Sensorwake, a new alarm clock on Kickstarter that gradually stimulates three of your senses to ease you into the day.

During the first minute of the alarm's three-minute wakeup process, it releases a pleasant aroma. You have your choice of scent cartridges, including cappuccino, peppermint, rose garden, chocolate factory, orange juice, and pine forest. A single cartridge lasts 30 days before it needs to be switched out.

After reviving your nose, Sensorwake activates its visual component: a soft light. For the final minute, the gadget plays sound like a traditional alarm clock, but instead of a blaring buzzer, you hear one of five upbeat melodies. If all that isn't enough to get you on your feet, you can hit snooze and wait for the cycle to start over in 10 minutes.

With more than three weeks left in its Kickstarter campaign, Sensorwake has already multiplied its original funding goal of $30,000. To reserve a clock and two scent capsules of your own, you can pledge $59 or more. Shipping is estimated for November of this year.

[h/t Mashable]

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Jason Dorfman, MIT CSAIL
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MIT’s New AI Can Sense Your Movements Through Walls Using Radio Signals
Jason Dorfman, MIT CSAIL
Jason Dorfman, MIT CSAIL

New artificial intelligence technology developed at MIT can see through walls, and it knows what you’re doing.

RF-Pose, created by researchers at the Computer Science and Artificial Intelligence Laboratory (CSAIL), uses wireless signals to estimate a person’s pose through a wall. It can only come up with a 2D stick figure of your movements, but it can nonetheless see your actions.

The system, described in a new paper [PDF], uses a neural network to piece together radio signals bouncing off the human body. It takes advantage of the fact that the body reflects radio frequency signals in the Wi-Fi range. These Wi-Fi signals can move through walls, but not through people.

Using data from low-power radio signals—1000 times lower than the power your home Wi-Fi router puts out—this algorithm can generate a relatively accurate picture of what the person behind the wall is doing by piecing together the signals reflected by the moving body.

The system can recognize movement in poor lighting and identify multiple different individuals in a scene. Though the technology is still in development, it’s not hard to imagine that the military might use it in surveillance, but the researchers also suggest that it may be useful for video game design and search-and-rescue missions. It might also help doctors monitor and analyze the movements of patients with disorders like Parkinson’s disease and multiple sclerosis.

This is just the latest in a series of projects using radio signals to mimic X-ray vision. CSAIL has been working on similar technology using Wi-Fi signals for several years, creating algorithms to recognize human forms and see motion through obstructions. In the future, they hope to expand the system to be able to recognize movement with 3D images rather than the current 2D stick figures.

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