The Stanford Artificial Intelligence Laboratory's Outreach Summer (SAILORS) program was born in 2014 when then-Ph.D. student Olga Russakovsky was in search of a way to make an impact outside of writing another research paper. What she and Fei-Fei Li, director of Stanford University's Artificial Intelligence Lab, created was a two-week summer day camp for 10th grade girls centered on how artificial intelligence can change the world. This July marked the second year of the program. "It seems like a lot of girls are interested in these fields, but then drop out as their education progresses," says Russakovsky. "We created a camp centered around teaching AI from a humanist prospective."

On a summer day in 1968, professor Julian Stanley met a brilliant but bored 12-year-old named Joseph Bates. The Baltimore student was so far ahead of his classmates in mathematics that his parents had arranged for him to take a computer-science course at Johns Hopkins University, where Stanley taught. Having leapfrogged ahead of the adults in the class, the child kept himself busy by teaching the FORTRAN programming language to graduate students. Unsure of what to do with Bates, his computer instructor introduced him to Stanley, a researcher well known for his work in psychometrics--the study of cognitive performance. To discover more about the young prodigy's talent, Stanley gave Bates a battery of tests that included the SAT college-admissions exam, normally taken by university-bound 16- to 18-year-olds in the United States.

The idea that we have brains hardwired with a mental template for learning grammar--famously espoused by Noam Chomsky of the Massachusetts Institute of Technology--has dominated linguistics for almost half a century. Recently, though, cognitive scientists and linguists have abandoned Chomsky's "universal grammar" theory in droves because of new research examining many different languages--and the way young children learn to understand and speak the tongues of their communities. That work fails to support Chomsky's assertions. The research suggests a radically different view, in which learning of a child's first language does not rely on an innate grammar module. Instead the new research shows that young children use various types of thinking that may not be specific to language at all--such as the ability to classify the world into categories (people or objects, for instance) and to understand the relations among things. These capabilities, coupled with a unique hu man ability to grasp what others intend to communicate, allow language to happen. The new findings indicate that if researchers truly want to understand how children, and others, learn languages, they need to look outside of Chomsky's theory for guidance. This conclusion is important because the study of language plays a central role in diverse disciplines--from poetry to artificial intelligence to linguistics itself; misguided methods lead to questionable results.

In 2013, Seth Lloyd, a professor of quantum information at Massachusetts Institute of Technology, put forward the idea of creating a "quantum enigma machine" -- one that would be modeled after the World War II-era cipher machines but would use quantum states of photons to encode and encrypt messages. Now, a team of researchers -- led by Daniel Lum, a graduate student at the University of Rochester, and John Howell, a professor of physics at the university -- have taken a step toward realizing this vision by actually demonstrating that an unbreakable encrypted message can be sent with a key that's far shorter than the message. This experiment, described in a new study published in the journal Physical Review A, violates what has hitherto been considered a fundamental rule of cryptography -- that a randomly generated key being used to encrypt a message needs to be at least as long as the message itself. It does so through a technique the researchers call "quantum data locking." The quantum enigma machine developed by the researchers consists of three parts -- a machine that generates photons, a spatial light modulator (SLM) that alters the amplitude and tilt of individual photons and also scrambles its wavefront, and an 8 by 8 photon detecting nanowire array.

Everyone who has ever read a piece of science fiction literature knows that humanity is going to employ more and more robots. They will work for us everywhere – in factories, in our homes, schools and so on. However, a new study from UCL and the University of Bristol has revealed that humans prefer having robots that are more expressive and emotional, even if it comes at a price of a lower efficiency. These results come as a surprise, because one would imagine that a robot is just a machine and its value can be judged by how well it accomplishes the tasks we assign to it. However, people look at robots in their close environment differently and they want them to be more human even if it means they make more mistakes.

Stepsize is a UK startup focused on developer tools. The firm is aiming to put a degree of Artificial Intelligence (AI) into DevOps. Stepsize Layer is a desktop application for developers that automatically adds context to code bases. It does this by hooking up tools used to develop software, structuring historical data and attaching this to the piece of code. This email address is already registered.

An unstoppable wave of automation is transforming the workplace. While many low-skill jobs are being eliminated, positions demanding higher skills are being created. Most jobs in existence today will add and lose specific functions in the future as robots and other forms of technology take on routine tasks and free humans to focus more on creative and analytic efforts, according to experts. It will be a messy transition. It will be particularly painful for workers who lose their jobs and for employers that fail to recognize where automation fits into their operations.

Artificial intelligence--the kind where robots understand a wide number of human concepts--has been a military focus for decades, and scientists in Japan may have just made a college-ready AI. For the first time, a Japanese artificial intelligence program has scored above average on a national standardized college entry exam, performing well enough to have an 80 percent likelihood of getting into 33 national universities, according to the National Institute of Informatics, or NII. The AI program scored 511 points out of 950 on the National Center Test for University Admissions (similar to the SATs), with a particularly strong performance in math and history, and well above the national average of 416. It was a first for the program, which performed less well in 2013 and 2014, according to the Wall Street Journal. NII announced the breakthrough on Saturday.

Sunil has created this guide to simplify the journey of aspiring data scientists and machine learning enthusiasts across the world. Through this guide, he will enable you to work on machine learning problems and gain from experience. He is providing a high level understanding about various machine learning algorithms along with R & Python codes to run them.

Attracting the best talent is the ultimate motive for recruiting professionals. In discussion with Mr. Adhiraj, Vice President (HR), ITC, we at CareerBuilder were acquainted with some innovative thoughts on how technology and recruiting would take place in 2015. "As technology continues to develop, can we assume that businesses will still be using recruiters 10 years from now? There are grounds for doubt, but it seems on the contrary that recruiters will have a highly strategic role to play in attracting and motivating the best talents for the projects, management and operations of the organizations they serve. One thing is certain, however: the digital transformation that began in 1995 with the advent of the Internet compels us to rethink everything.