As part of my Data Science class with General Assembly, we each gave a presentation about a real-world application of data science. My talk was about using machine learning to detect fraud on Skype, and was based upon an excellent paper by Microsoft Research published in November 2013. Although Skype already had measures in place to detect fraud (e.g., credit card fraud, spam instant messages), the research team's goal was to improve the detection of "stealthy fraudulent users" that evade Skype's defenses for a prolonged period. They built a machine learning classifier that flagged potentially fraudulent users, and was able to detect 68% of these users with a false positive rate of 5%. The novelty in their approach was the fusing of disparate data types (profile information, Skype product usage, and Skype social activity) into a single classifier.

When in 2012 a computer learned to recognize cats in YouTube videos and just last month another correctly captioned a photo of "a group of young people playing a game of Frisbee," artificial intelligence researchers hailed yet more triumphs in "deep learning," the wildly successful set of algorithms loosely modeled on the way brains grow sensitive to features of the real world simply through exposure. Using the latest deep-learning protocols, computer models consisting of networks of artificial neurons are becoming increasingly adept at image, speech and pattern recognition -- core technologies in robotic personal assistants, complex data analysis and self-driving cars. But for all their progress training computers to pick out salient features from other, irrelevant bits of data, researchers have never fully understood why the algorithms or biological learning work. Now, two physicists have shown that one form of deep learning works exactly like one of the most important and ubiquitous mathematical techniques in physics, a procedure for calculating the large-scale behavior of physical systems such as elementary particles, fluids and the cosmos. The new work, completed by Pankaj Mehta of Boston University and David Schwab of Northwestern University, demonstrates that a statistical technique called "renormalization," which allows physicists to accurately describe systems without knowing the exact state of all their component parts, also enables the artificial neural networks to categorize data as, say, "a cat" regardless of its color, size or posture in a given video.

Tess. is a London-based online service created for women that offers personalized professional styling recommendations based on artificial intelligence. of 5 (Photo: MyTess/Dasha Egay) Today, artificial intelligence has become the latest trend in various fields, including education, healthcare, the environment and the business sectors. But have you ever wondered what it would be like if artificial intelligence invades the world of fashion? Whether people will admit it or not, fashion is playing an essential role in our daily routines. Since we are currently in an era where artificial intelligence is on the rise, some of us can't help but wonder how AI will change and influence the world of fashion. Earlier in May, people got a glimpse of how experts incorporated artificial intelligence into the ever-evolving field of fashion.

A really cool way to engage an audience is using live polls in your PowerPoint presentations. What's great about this is if you ask the audience a question, instead of having them shout out their answers or writing their responses on a flip chart, you can have them respond on their mobile devices so you can see the results appear in real time on the slide. This can work with all types of questions – from multiple choice, to free response, to (my favorite) word clouds. Watch the video below or scroll down the page to see how to get started with live polling in PowerPoint today.

An artifical intelligence (AI) diagnosis for eye disease is becoming more likely with Google's DeepMind. Computerworld reports that Google's AI business unit is using patient data from a U.K. hospital in an effort to teach computers how to detect early warning signs of sight loss. Although some hurdles currently exist in implementing health care AI, initiatives like this have potential to transform the future of patient care. The traditional way doctors look for certain eye diseases is to examine an area of the eye called the fundus by either using an ophthalmoscope or by taking a digital fundus scan. Optical coherence tomography is another diagnostic technique that uses a noninvasive, three-dimensional scan of the retina, according to Computerworld.

Artificial intelligence is going to transform "massive swaths" of the workplace, LinkedIn co-founder Reid Hoffman said Thursday. And its effects will be felt beyond sectors like manufacturing and energy, reaching into professional spheres like doctors, lawyers and financial analysts, he said. "It could have very positive effects, but it has very dynamic effects. Yes, jobs will be going away. We've got to focus on entrepreneurship and creating new jobs," he said in an interview on CNBC's "Closing Bell."

The Duchess of Cambridge, Kate Middleton, will not only make you fall in love with her timeless charms and classic beauty. Her sense of humor and fun personality would make you understand why Prince William fell in love with her. Middleton showed the crowd her funny side during a gala event by one of their friends held on June 22. An interesting reason behind her humor might shock most of the people. People Magazine reported how Kate Middleton kid around the chefs of the said event saying Prince William is patient enough to put up with her cooking.

"Nature hath made men so equal, in the faculties of the body, and mind; as that though there be found one man sometimes manifestly stronger in body, or of quicker mind than another; yet when all is reckoned together, the difference between man, and man, is not so considerable, as that one man can thereupon claim to himself any benefit, to which another may not pretend as well as he." This peculiar thought--that, in the most important respects, and despite their manifest differences, all men are equal--has laid the intellectual foundation for democracy's unlikely triumph. But will society retain its belief in equality when it is no longer just man against man? Can democracy thrive when more and more benefits accrue to machines that are stronger in body, and quicker in mind, than any mere mortal? And will the machines' owners remain willing to honor the claims of their social inferiors when they no longer need them to make their food, or to staff their companies, or to fight their wars?