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How AI Could Track and Use Your Emotions

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Artificial intelligence can now gauge human emotions, and it's being used in everything from education to marketing, experts say. Your emotions could potentially be tracked using your Wi-Fi router and analyzed by AI, according to a new study from London's Queen Mary University. Researchers used radio waves like those used in Wi-Fi to measure heart and breathing rate signals, which could determine how a person is feeling. The study shows just how pervasive emotion-monitoring could become. "In education, AI could be used in adapting content to serve the needs of each child best," Kamilė Jokubaitė, CEO and founder of Attention Insight, who was not involved in the study, said in an email interview.


Beating Back Cancel Culture: A Case Study from the Field of Artificial Intelligence

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It's easy to decry cancel culture, but hard to turn it back. And as I explain below, the lessons that members of the AI community have learned in this regard can be generalized to other professional subcultures. To understand the flash point at issue, it's necessary to delve briefly into how AI functions. In many cases, AI algorithms have partly replaced both formal and informal human decision-making systems that pick who gets hired or promoted within organizations. Financial institutions use AI to determine who gets a loan. And some police agencies use AI to anticipate which neighborhoods will be afflicted by crime.


Data Transformers Podcast: Is Video Artificial Intelligence Ready for Prime Time? on Apple Podcasts

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Video AI is a growing market with lots of innovation. The Video AI market encompasses Video surveillance, Automatic/self-drive vehicles, content moderation in video, automatic video editing. Convolution Neural Networks is the backbone of Video AI in many applications and the challenge lies in training the data as well as abstracting the outcomes for better outpost. The field is still emerging and the technology is still evolving in many of these areas. As an example, even though Youtube would like to have a general understanding of the video so they know when to insert relevant ads, the technology to do that is just emerging.


New microcomb could help discover exoplanets and detect diseases

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Tiny photonic devices could be used to find new exoplanets, monitor health, and make the internet more energy efficient. Researchers from Chalmers University of Technology, Sweden, now present a game-changing microcomb that could bring advanced applications closer to reality. A microcomb is a photonic device capable of generating a myriad of optical frequencies--colors--on a tiny cavity known as a microresonator. These colors are uniformly distributed so the microcomb behaves like a'ruler made of light." The device can be used to measure or generate frequencies with extreme precision. In a recent article in the journal Nature Photonics, eight Chalmers researchers describe a new kind of microcomb on a chip, based on two microresonators. The new microcomb is a coherent, tunable and reproducible device with up to 10 times higher net conversion efficiency than the current state of the art. "The reason why the results are important is that they represent a unique combination of characteristics, in terms of efficiency, low-power operation, and control that are unprecedented in the field," says Óskar Bjarki Helgason, a Ph.D. student at the Department of Microtechnology and Nanoscience at Chalmers, and first author of the new article. The Chalmers researchers are not the first to demonstrate a microcomb on a chip, but they have developed a method that overcomes several well-known limitations in the field. Placed on a chip, the newly developed microcomb is so small that it would fit on the end of a human hair. The gaps between the teeth of the comb are very wide, which opens great opportunities for researchers and engineers. Since almost any measurement can be linked to frequency, the microcombs offer a wide range of potential applications. They could, for example, radically decrease the power consumption in optical communication systems, with tens of lasers being replaced by a single chip-scale microcomb in data center interconnects. They could also be used in lidar for autonomous driving vehicles, for measuring distances. Another exciting application for microcombs is the calibration of spectrographs used in astronomical observatories devoted to the discovery of Earth-like exoplanets. Extremely accurate optical clocks and health-monitoring apps for mobile phones are further possibilities. By analyzing the composition of exhaled air, clinicians could potentially diagnose diseases at earlier stages. "For the technology to be practical and find its use outside the lab, we need to co-integrate additional elements with the microresonators, such as lasers, modulators and control electronics.


Can Artificial Intelligence Bring an End to Cyberbullying?

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Before we were so connected by technology, bullying was most frequently identified in school settings. For example, remember Scut Farkus in "A Christmas Story" or Brian Johnson (Anthony Michael Hall's character) in "The Breakfast Club?" But Bullying is not just for kids. Harassment and hate speech exists in the workplace and socially among adults. So, what's changed, and what can be done about it? Online activity, such as social media, texting, and gaming, provides constant contact and further reach with our peers, colleagues, friends, and even strangers.


Can AI get common sense? Facebook model shows the way

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San Francisco: In an advance to building machines with common sense, Facebook researchers have developed a new Artificial Intelligence (AI) model that can learn from any random group of images on the Internet without the need for careful curation and labelling that goes into most computer vision training today. Called SEER (Self-supERvised), the "self-supervised" computer vision model was fed on a billion random, unlabelled and uncurated public Instagram images, Facebook said on Thursday. The future of AI is in creating systems that can learn directly from whatever information they are given -- whether it is text, images, or another type of data -- without relying on carefully curated and labelled data sets to teach them how to recognise objects in a photo, interpret a block of text, or perform any of the countless other tasks that we ask it to. This approach is known as self-supervised learning. According to Facebook AI's Chief Scientist Yann LeCun, the self-supervised learning approach is one of the most promising ways to build machines that have the background knowledge, or "common sense," to tackle tasks that are far beyond today's AI.


Your Dating App Data Might Be Shared With the U.S. Government

Slate

When you download a dating app, fill out a profile with some of your most private information, and select "allow app to access location" to locate nearby potential love interests, you may feel a little exposed, but you proceed anyway, in order to find those dates. But there is reason to believe that by using these sites, you may be unknowingly submitting to government tracking--and we can't know for sure because of all of the secrecy involved with deals that data brokers make with government agencies. It's yet another demonstration of the need to bring transparency to the data-collection industry. Dating apps ask users for a variety of highly personal information and retain it indefinitely, potentially forever. This can include photos and videos, text conversations with other users, and information on gender, sexual orientation, political affiliation, religion, desire to have children, location, HIV status, and beyond.


Jobs You Can Add to Your Résumé as a Single Person

The New Yorker

With the time and effort it requires, sometimes dating can feel like a job––but, unfortunately, saying that you're single does nothing for your résumé. Here are a few ways to adapt your dating experiences into professional, C.V.-worthy titles and descriptions. Selecting from a mix of seasoned stars and aspiring hopefuls, I judge the performance and competence of prospects vying for the role. They audition for me, and I insure that only the most talented move forward. I am in charge of seeking out and acquiring the best partnerships for the brand.


The Future of IoT is AI

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It is true that IoT or Internet of Things revolution is going on, and AI or Artificial Intelligence can play a vital role in it. The goal of applying AI to IoT systems is effectively placing an additional layer of intelligence across the entire IoT stack -- from infrastructure all the way to applications. The Internet of Things (IoT) is a term that has been introduced in recent years to define objects that are able to connect and transfer data via the Internet. 'Thing' refers to a device that is connected to the internet and transfers the device information to other devices. The cloud-based IoT is used to connect a wide range of things such as vehicles, mobile devices, sensors, industrial equipment and manufacturing machines to develop various smart systems it includes smart city and smart home, smart grid, smart industry, intelligent vehicle, smart health, and smart environmental monitoring.


How to make data scientists shine

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The effort to take advantage of emergent new business innovations, of advances in digitization, analytics, artificial intelligence, machine learning, internet of things or robotics, is leading to an increasing demand for people with related skills. Being a data scientist may be considered as the sexiest job within the data related jobs, but it has its challenges, specially when it comes to demonstrate the value created by their work. In this article, let us look at some of those challenges, and how they can be overcome when organizations take on a systematic approach on how to manage their data. This is often a communication problem, turning a business problem into a technical problem, when there is a gap in the language and concepts used by the business stakeholders and the data scientists. However, the causes run deeper, and can be related also with a lack of data literacy on the business side and business literacy on the data side, and with the lack of organization wide business concepts that can be clearly mapped into data.