Soon, the glow of hundreds of screens illuminates each face in every classroom. Inside Skye Templeton's seventh-grade Social Studies class, students are enthralled by online documents and videos about the casualties of World War II. Nearby, in Sara Sharpe's sixth-grade math class, a small group of students works through computer drills covering ratios and percents. And, across the hallway, English and Language Arts teacher Lori Meyer expresses amazement at how much her eighth graders enjoyed doing their final project: a research paper and iMovie on the 1960s. With their MacBooks, students researched topics, wrote their papers, and submitted to their teacher via email. "This is the first time in my 12 years of teaching that students said writing the research paper was their favorite assignment," Meyer said, "and I know it was due to the laptops."

Researchers are developing a personalised privacy assistant app that can simplify the task of setting permissions for your smartphone applications. That is a job that requires well over a hundred decisions, an unmanageable number for the typical user, researchers from Carnegie Mellon University (CMU) in the US said. The privacy assistant can learn the user's preferences and quickly recommend the most appropriate settings, such as with which app to share the user's location, or contact list. In the field test, people accepted almost 80 per cent of the recommendations made by the privacy assistant and, at the end of the study, these people indicated they were more comfortable with their privacy settings than users who did not have a privacy assistant, researchers said. "It is clear that people just cannot cope with the complexities of privacy settings associated with the apps they have on their smartphones," said Norman Sadeh from CMU.

Ever since the late 1950s, when pioneering IBM researcher Arthur Samuel trained the world's first self-learning computer to play a mean game of checkers, the future has promised a widespread emergence of intelligent machines. Machine learning, the computing methodology Samuel introduced to the world, is now seen as mature, effective and -- thanks to a variety of new offerings -- readily accessible to the channel. "For consulting companies like ours, this is the opportunity of a lifetime," said Dj Das, CEO of Third Eye Consulting Services and Solutions, a big data and analytics solution provider in Santa Clara, Calif., that partners with four major hyper-scale cloud providers: IBM, Microsoft, Google and Amazon Web Services. That opportunity has presented itself in a diverse spectrum of use cases, from optimizing supply chains, predicting customer buying patterns, diagnosing illnesses, detecting fraud, recognizing text and images, and improving IT performance and security. "The clients I talk to, the partners I talk to, they understand that this is going to be a disrupter," Ed Harbour, IBM's vice president for implementations for Watson, Big Blue's cloud-based cognitive computing platform, told CRN. "And whether they choose to embrace it to their advantage or whether they don't is probably going to determine the outcome of how their businesses go forward." IBM is staking much of its future on cognitive computing, an analytic approach that mimics human thought processes of which machine learning is an essential component.

Tom Murphy graduated from Carnegie Mellon University with a PhD in computer science. Then he built software that learned to play Nintendo games. In some cases, the system works well. Playing Super Mario, for instance, it learns to exploit a bug in the game, stomping on enemy Goombas even when floating below them. It can rack up points by attacking the game with a reckless abandon you and I would never try.

Artificially intelligent beings, once portrayed in celluloid as gigantic machines inside mammoth control rooms, are now a part of every smartphone (virtual assistants). And as I write this post, technology bigwigs and startups alike are tirelessly engaging in the effort to build the perfect virtual assistant for everyone. In their powerful endeavor, they have been strongly aided by the power of inexpensive, computing platforms in the form of the smartphones. Significant advancements in speech recognition algorithms have also contributed to the optimism. Those who understand technology will also appreciate the fact that access to data through web APIs has also boosted the research and outcome in the domain.

As I write this, I'm listening to music written and performed by a robot that was built by Brain.fm to help me focus. I think it might be working, giving me a tiny buzz. It could of course be a placebo effect. In fact, the fact that I even wrote that last three-word sentence should tell you something about the attitude in which I approached Brain.fm's Brain.fm is a new audio startup out of Chicago that produces music written by artificial intelligence that promises to get your brain into one of several desired states, from deep sleep to focused work.

It's odd holding a minute's silence for a dead person who you never knew anything about, especially at a tech show where you can see messages from their AI reincarnation flashing up on a massive screen behind the very-much-alive woman who has made this whole strange scene possible. Is this what a 21st-century Dr Frankenstein looks like? Except now, instead of stitching body parts together to recreate life, what we're seeing is found fragments of the deceased's personality put through a form of machine learning to create a semblance of their life after death. Very recently however, Luka was adapted in a brand new way, to include a chatbot based on a real human being--one who just so happens to be dead. It's this ghost-in-the-machine that has the audience spellbound, as Luka's cofounder Eugenia Kuyda explains how text messages, social media conversations, and other sources of information on the deceased were grafted onto an existing AI platform.

Sandia National Laboratories is the nation's premier science and engineering lab for national security and technology innovation with major facilities in Albuquerque, New Mexico and Livermore, California. We are a world-class team of scientists, engineers, technologists, post docs, and visiting researchers all focused on cutting-edge technology, ranging from homeland defense, global security, bio...technology, and environmental preservation to energy and combustion research, computer security, and nuclear defense. To learn more, please visit our website at www.sandia.gov. We are searching for a Manager for the Semiconductor Device Sciences Department for the Albuquerque facility. Must be able to obtain and maintain a DOE Security Clearance.

SINGAPORE: At a time when radicalism is on the rise and people are concerned that their city might join the list of those tainted by terror, safety and security are topmost on the minds of government customers, Hewlett Packard Enterprise told Channel NewsAsia. The US-based IT giant is thus hoping to tackle these issues with a tool to help governments better make sense of the huge amounts of information being shared online by citizens, in the form of a Citizen Insights Dashboard. The tool, which is currently in beta, will be showcased for the first time at the World Cities Summit (WCS) held in Singapore from Sunday (Jul 10). It was developed in the city-state since April by a team led by Mr Jason Tan, director of HSE Insights Lab Singapore spearheading the project. More than just surveillance for security, the dashboard looks to make sense of posts made by citizens on social media to understand their thoughts and what they care about.

Researchers from the University of Southern California have developed a new machine learning tool capable of detecting certain speech-related diagnostic criteria in patients being evaluated for depression. Known as SimSensei, the tool listens to patient's voices during diagnostic interviews for reductions in vowel expression characteristic of psychological and neurological disorders that may not be sufficiently clear to human interviewers. The idea is (of course) not to replace those interviewers, but to add additional objective weight to the diagnostic process. The group's work is described in the journal IEEE Transactions on Affective Computing. Depression misdiagnosis is a huge problem in health care, particularly in cases in which a primary care doctor making (or not) the diagnosis.