Walmart’s New AI-Camera Technology Can Prevent Theft at Checkout

Image Source: iStock.com/artran

Computer vision technology has been implemented in over 1,000 Walmart stores. This type of technology is called the Missed Scan Detection which helps checkout registers recognize if items have passed by the scanner without being scanned and immediately notifies the attendant. Walmart’s surveillance system is being upgraded by applying this new technology at their kiosk stations and their registers. 

AI is surely becoming a part of our everyday lives as large retailers like Walmart begin to rely on these systems for daily operations. The ultimate goal of computer vision technology is to prevent revenue loss and theft, which, in 2017, turned out to be a big problem for many U.S. retailers who lost up to $47 billion. Since the system was installed, Walmart stated that they have had decreased theft, losses, and errors.

Walmart hasn’t been the only large retailer to use AI. Amazon has been investing in Artificial Intelligence as well, however, the approach is a little different. They have produced a smooth and cashier-less experience for their customers in their own Go stores. 

Aside from it’s anti-theft technology, Walmart also recently opened an AI-powered store to supervise their large inventory. This makes it easier for employees to keep track of when stocks are running low and order items on time before supply runs out.

The AI Tech Mastermind Behind “ThisPersonDoesNotExist.com” is Now Creating Fake Animals and Home Listings

Image Source: BBC

ThisPersonDoesNotExist.com creates pictures of human faces who look like everyday people that we come across. However, as the website domain so explains: these people do not exist. All the faces on the website are 100% fake and are completely computer-generated. To create these faces, the website uses a GAN, or generative adversarial network.

The Next Web states that GAN uses two methods that work against one another – the judge and generator. The generator’s task involves misleading the judge into thinking a generated photo is legitimate. If the judge is fooled by the generator, a developer takes a look at the coding algorithm. The GAN steps in to tell us when the generator is favorable. This website uses a certain type of method, StyleGAN – created by an Artificial Intelligence company, Nvidia –  to generate thousands of fake faces, each individually shown through every refresh page button press.

StyleGAN has now expanded into websites that generate fake cats (TheseCatsDoNotExist.com), fabricated anime characters (ThisWaifuDoesNotExist.net), and phony Airbnb listings (ThisAirbnbDoesNotExist.com). One of the website developers explained that the reasoning behind these fruitless websites is to show people how easily they can be convinced into believing something that is not real. Websites like these could now be used to fabricate nearly anything, whether it’s a bogus news story or if it’s a nonexistent person.

Chris Schmidt, owner of ThisAirbnbDoesNotExist.com, stated,This means that just about anyone with a couple hours to kill could create something just as compelling as I did…[AI is] now sufficiently advanced that they can often fool folks, especially if they’re not looking very hard.”

Artificial Intelligence Can Predict Your Identity by Simply Scanning Your Eyes

You can really tell a lot by just looking into someone’s eyes.

According to a study involving Artificial Intelligence done between the University of South Australia and the University of Stuttgart, this will be the first time ever that personality traits can be identified using your eye movements, as the algorithm software reliably recognizes four of the Big Five personality traits: neuroticism, extraversion, agreeableness, and conscientiousness. The goal is to improve human and robot interactions at some point near the future more natural and be better at interpreting human social signals.

Machine-learning calculations algorithms interfaces between eye developments and four of the enormous five identity qualities.

“Eye movements are also a window into our mind and a rich source of information on who we are, how we feel and what we do,” the study stated.

By giving credit to their machine-learning approach, not only did they validate the role of personality in explaining eye movement in everyday life, but they also uncovered new eye movement techniques to find out ones’ personality traits.

This project had an artificial intelligence machine track and monitor the eye movement of almost 42 human volunteers using a video-based-eye-tracker from a sensomotoric instrument.

That’s where the machine-learning techniques came in: The artificial intelligence interpreted information such as blink rate, blink duration, dwelling time on an object and visual heat maps to make guesses about an individual’s traits. Then, to confirm the AI’s guesswork, researchers had study participants take personality questionnaires that are already well-known in the research community

“This research provides opportunities to develop robots and computers so that they can become more natural, and better at interpreting human social signals.”


In a world where companies and labs are working hard on humanoid hospital nurses — or even sex robots — it’s easy to see where this kind of technology could be used. Imagine a robotic hospital worker adjusting its approach to treatment depending on what it infers about a patient’s personality — or a personal assistant device that learns not to set off our neurotic side.

In the end, scientists found that the AI was able to make reliable guesses about such traits as neuroticism, extraversion, agreeableness and conscientiousness. Not only does it demonstrate that AI can possibly read us like books, yet it demonstrates that our eyes could really be entryways to our souls.

You can read more about this new technique here.

 

Shoplifters Beware: Japan’s AI Security Cam Technology Will Be the Future of Automated Surveillance

Thanks to Japan’s latest AI technology from telecom company NTT East and startup Earth Eyes Corp, automated surveillance CCTV cameras now have the ability to detect suspicious behavior to catch a thief in action.

Called the “AI Guardman,” this new surveillance technology could really change the game in terms of assisting shop owners with safeguarding their merchandise from unlawful hands. By using open source technology as developed by Carnegie Mellon University, the AI has the capability of scanning live video to approximate body positions or poses. With that information collected, the system then works by matching the poses to predefined “suspicious” body movements (e.g., putting a shelf item in a bag or pocket). If the system makes a match, shopkeepers are alerted through its connected app.

While it has been a few years since the start of AI Guardman’s development, both NTT East and Earth Eyes have only recently released results of the technology’s early trials. As some excellent news, Japan’s IT Media reports that shoplifting in stores has decreased by around 40% ever since the device’s implementation in stores.

With the help of new technology’s deep learning abilities, video footage analyzation has become quicker and easier. Multiple companies in Japan, America, and China have all begun developing products with such capabilities, with businesses like Amazon and Nest using their own version of AI analysis in their home security camera products.

What is different about AI Guardman, however, is the fact that its setup time greatly varies from other security systems, as the camera can simply be plugged in and ready to use. NTT East’s spokesperson notified The Verge media site about its set price of around $2,150, with a fee of $40 per month for cloud support. The AI Guardman is set to go on sale towards the end of July, and as NTT explains, “Our primary target [for the device] is big businesses although we do not have the intention to omit small ones.”

Though automated surveillance may have its benefits, it most certainly comes with its drawbacks in terms of privacy, accuracy, and discriminatory issues. While the AI can screen and match certain body movements/poses to “suspicious” behavior, some situations are reliant on context. For example, the AI misidentifies salesclerks restocking shelves and indecisive buyers (who pick up and put down items multiple times) as shoplifters, providing for a lot of potential false positives. Training data used may also be biased towards a certain group of people, making way for discriminatory practice, although NTT East denied such possibilities, explaining how the AI Guardian “does not find pre-registered individuals.”

With AI technology growing more and more popular as the tool of the future, researchers are also working on automated surveillance that goes beyond the store walls, using the technology to spot violent behavior within a crowd, for example. Such analysis provided by AI can surely be a positive force in keeping people safe during massive crowd events in which precautionary measures must be taken against potential threats. The next time you find yourself walking past a CCTV cam, you could be asking if it’s really AI on the other side.

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