Researchers have found that children become better at math if their whole bodies are engaged while learning. They also found that many children improve at math if the way it's taught is individualized to each child. The research could have an impact on new teaching methods and the incorporation of physical activity during the school day. The study, conducted by researchers at the University of Copenhagen's Department of Nutrition, Exercise and Sports, investigated whether different types of math learning strategies change the way children solve math problems. The research, published in the journal Frontiers in Human Neuroscience, was conducted over a six-week period and involved testing the mathematical abilities of school children with an average age of seven years old.

Actor, director, model, teen vampire movie star – now Kristen Stewart can add research author to her list of credentials. Stewart, best known for her portrayal of Bella Swan in the Twilight Saga films, has co-written an article published in Cornell University's online library arXiv. It explains the artificial intelligence technique used in her new short film, Come Swim, that enables footage to take on the visual appearance of a painting. Kristen Stewart, best known for her portrayal of Bella Swan in the Twilight Saga films, has co-written an article published in Cornell University's online library arXiv Many popular software programs, such as Adobe Photoshop and GIMP, already provide filters that can make photographs take on the general style of oil paintings, pen sketches, screen-prints or chalk drawings, for example. The algorithms needed to accomplish this first began to produce aesthetically pleasing results in the early 1990s.

Two of the biggest trends in technology right now are machine learning and artificial intelligence. In fact, the two terms are used almost interchangeably. However, there are subtle but important differences between them both. In many ways, machine learning is a subset of artificial intelligence. Also, the term AI is older than machine learning.

Things are going insanely well for people in computer science. I mean, our work is everywhere. Nearly every process imaginable is powered by a machine at the middle. The computer has transformed communication, retail, how we access information and how we navigate around the world. Things are even better in A.I. We are at the beginning of a renaissance of interest and utilization of intelligent systems in an ever-widening sphere of influence.

Do you remember the first time you saw a picture of a cat? You were probably a baby, and it's likely that you didn't comprehend that what you were looking at was a cat. But then days and years went by, and during that time you saw many more pictures of cats, and maybe even a few real cats. You saw a lot of things that you were told weren't cats. And one day, without being prompted, you saw a picture of a cat and thought, "That's a cat!"

Many of them are new to this set of technologies, and seeing the topic through my students' eyes has made me realize how overwhelming it can be. There are so many different types of AI, each requiring some technical knowledge to fully grasp, that newcomers to the field often have difficulty figuring out how to jump in. In the simplest case, cognitive technologies can be just more autonomous extensions of traditional analytics -- automatically running every possible combination of predictive variables in a regression analysis, for example. More complex types of cognitive technology -- neural or deep learning networks, natural language processing, and algorithms -- can seem like black boxes even to the data scientists who create them. Though these technologies can seem daunting, the good news is that getting started with cognitive technologies is getting easier all the time.

Skin cancer is the most commonly diagnosed cancer in the United States. Over five million cases are diagnosed each year, costing the U.S. healthcare system over $8 billion. More than 100,000 of these cases involve melanoma, the deadliest form of skin cancer, which leads to over 9,000 deaths a year, and the numbers continue to grow. Internationally, melanoma also poses a major public health threat. In Australia, there are over 13,000 new instances of melanoma yearly, leading to more than 1,600 deaths.

In our sequel to the 2015 Puerto Rico AI conference, we brought together an amazing group of AI researchers from academia and industry, and thought leaders in economics, law, ethics, and philosophy for five days dedicated to beneficial AI. We hosted a two-day workshop for our grant recipients to give them an opportunity to highlight and discuss the progress with their grants. We followed that with a 2.5-day conference, in which people from various AI-related fields hashed out opportunities and challenges related to the future of AI and steps we can take to ensure that the technology is beneficial. Honoring the FrieNDA for the conference, we are only posting videos and slides below with approval of the speaker. Learn more about the Asilomar AI Principles that resulted from the conference and the process involved in developing them.

The recently published "Ethically Aligned Design," a 136-page report by IEEE, boldly goes where no report has gone before, with more than 225 mentions of ethical issues surrounding the development of artificial intelligence and autonomous systems. That's in contrast to other reports, like the "One Hundred Year Study on Artificial Intelligence (AI100)," published last year by Stanford. "AI100" stated, "The difference between an arithmetic calculator and a human brain is not one of kind, but of scale, speed, degree of autonomy, and generality." That frightening statement makes clear that the "AI100" authors did not appreciate what the IEEE report's authors so clearly understand: People are not machines, and machines are not people. The authors of "Ethically Aligned Design" assume that there are "users" and there are "systems," and that excellence in design is when users are well served by their systems.

When we think about robots, we often think of humanoid helpers like in the Jetsons (it's a cartoon that older people distinguished people would have watched growing up) or massive industrial automatons that build those Teslas you see whizzing around these days. Maybe instead, we are reminded of a looming job crisis, where machines threaten to steal our livelihoods. In any case, "serious" industries with "serious" challenges are generally at the forefront of discussions about robotics because the technology involved has been research-driven and resource-intensive. This seems not to be the major hurdle anymore, and a lighter and rather cool branch of robots are taking over our living rooms: toys. Still, toys aren't often thought of as lucrative investment opportunities.