Mobile robots can help chronically ill children regain part of the normal school experience. Some kids are unable to attend school for months or even years due to symptoms, treatments, or recovery from serious illness. These homebound children typically continue their education by having make-up work sent home and (depending on resources) studying with tutors for a few hours each week. But they miss out on a key aspect of school: socialization. With today's technology, the definition of face time has changed.

When you think about it, not a lot has changed in the legal world from the days of To Kill A Mockingbird to the latest John Grisham thriller. Sure, literature snobs may insist that Atticus Finch's flawless moral heroism should never be compared to the conflicted protagonists of contemporary legal page-turners, but in terms of the substance of how lawyers do their lawyering, the fundamentals have barely changed in 80 years, from the career track of a young lawyer to the set-up of a law firm. The same cannot be said of virtually any other profession. Indeed, the legal industry seems more dusty than dynamic; the robes and wrinkles that mark those at the top of the field hardly scream modernity. But change is afoot, as a couple of powerful market forces are driving law firms to adopt modern corporate efficiency.

I teach one of the world's most popular MOOCs (massive online open courses), "Learning How to Learn," with neuroscientist Terrence J. Sejnowski, the Francis Crick Professor at the Salk Institute for Biological Studies. The course draws on neuroscience, cognitive psychology, and education to explain how our brains absorb and process information, so we can all be better students. Since it launched on the website Coursera in August of 2014, nearly 1 million students from over 200 countries have enrolled in our class. We've had cardiologists, engineers, lawyers, linguists, 12-year-olds, and war refugees in Sudan take the course. We get emails like this one that recently arrived: "I'll keep it short. I've recently completed your MOOC and it has already changed my life in ways you cannot imagine. I just turned 29, am in the middle of a career change to computer science, and I've never been more excited to learn."

When Pyotr Stolyarsky died in 1944, he was considered Russia' s greatest violin teacher. He counted among his pupils a coterie of stars, including David Oistrakh and Nathan Milstein, and a school for gifted musicians in his native Odessa was named after him in 1933. But Stolyarsky couldn't play the violin anywhere near as well as his best students. What he could do was whisper metaphors into their ears. He might lean over and explain how his mother cooked Sabbath dinner.

Walter Pitts was used to being bullied. He'd been born into a tough family in Prohibition-era Detroit, where his father, a boiler-maker, had no trouble raising his fists to get his way. One afternoon in 1935, they chased him through the streets until he ducked into the local library to hide. The library was familiar ground, where he had taught himself Greek, Latin, logic, and mathematics--better than home, where his father insisted he drop out of school and go to work. Outside, the world was messy. Inside, it all made sense. Not wanting to risk another run-in that night, Pitts stayed hidden until the library closed for the evening. Alone, he wandered through the stacks of books until he came across Principia Mathematica, a three-volume tome written by Bertrand Russell and Alfred Whitehead between 1910 and 1913, which attempted to reduce all of mathematics to pure logic. Pitts sat down and began to read. For three days he remained in the library until he had read each volume cover to cover--nearly 2,000 pages in all--and had identified several mistakes. Deciding that Bertrand Russell himself needed to know about these, the boy drafted a letter to Russell detailing the errors.

Nineteen stories up in a Brooklyn office tower, the view from Manuela Veloso's office--azure skies, New York Harbor, the Statue of Liberty--is exhilarating. But right now we only have eyes for the nondescript windows below us in the tower across the street. In their panes, we can see chairs, desks, lamps, and papers. The genuine objects are in a building on our side of the street--likely the one where we're standing. A bright afternoon sun has lit them up, briefly turning the facing windows into mirrors. We see office bric-a-brac that looks ghostly and luminous, floating free of gravity. Veloso, a professor of computer science and robotics at Carnegie Mellon University, and I have been talking about what machines perceive and how they "think"--a subject not nearly as straightforward as I had expected. "How would a robot figure that out?" she says about the illusion in the windows.

AIED is an interdisciplinary community at the frontiers of the fields of computer science, education and psychology. It promotes rigorous research and development of interactive and adaptive learning environments for learners of all ages, across all domains. The society brings together a community of members in the field through the organization of Conferences, a Journal, and other activities of interest. The International AIED Society is governed by an Executive Committee according to the IAIED Constitution, which seeks to support AI in Education developments throughout the international community. Membership statistics show that over 1000 members from 40 countries have joined since the Society's launch on January 1 1997.

Artificial Life Researcher; Creator of Lucy, a Robot Babay Orangutan; Author, Creation: Life and How to Make It. Physicist, Universite' de la Mediterrane' (Marseille, France); Author: What is time?

The platform is providing a holistic online solution for teachers, students, and parents. Over two decades ago, Educomp set out to change the entire education system in the country. Since then, it claims to have empowered over 30 million learners and educators across over 65,000 schools. While Educomp was continuing to overhaul the education ecosystem through its smart class programmes, the top leadership in the company realised that they needed to take education beyond the conventional classrooms. Now, instead of taking students to classrooms, they had to flip the normal course and take classrooms to students, beyond boundaries.

Online learning with streaming data in a distributed and collaborative manner can be useful in a wide range of applications. This topic has been receiving considerable attention in recent years with emphasis on both single-task and multitask scenarios. In single-task adaptation, agents cooperate to track an objective of common interest, while in multitask adaptation agents track multiple objectives simultaneously. Regularization is one useful technique to promote and exploit similarity among tasks in the latter scenario. This work examines an alternative way to model relations among tasks by assuming that they all share a common latent feature representation. As a result, a new multitask learning formulation is presented and algorithms are developed for its solution in a distributed online manner. We present a unified framework to analyze the mean-square-error performance of the adaptive strategies, and conduct simulations to illustrate the theoretical findings and potential applications.