We are experts in Smart Machines, Robotics, Internet of Things and Innovation. Through the Bill and Melinda Gates Foundation, Microsoft's co-founder and chairman has invested more than 240 million to date in a developing field known as "personalized learning." Linden, the creator of the Second Life online world, is creating a new platform dubbed Project Sansar, an online virtual world that will be viewable with a variety of VR headsets.

Andrew Moore was a professor of computer science and robotics at Carnegie Mellon University for a dozen years when Google hired him away in 2006 to lead some of its efforts around ad targeting and fraud prevention. CMU lured Moore back in 2014, making him the dean of its computer science school. But he still understands well what goes through his colleagues' minds when industry comes calling, and he says the battle to keep them in academia grows fiercer by the year. Earlier today, we talked with Moore about Uber, which famously raided the school's robotics department a year ago, poaching 40 of its researchers and scientists. We also talked about how Moore entices people to stay, and the newest new thing his 2,000-student school is focused on right now.

The ACM constitution provides that our Association hold a general election in the even-numbered years for the positions of President, Vice President, Secretary/Treasurer, and Members-at-Large. Biographical information and statements of the candidates appear on the following pages (candidates' names appear in random order). In addition to the election of ACM's officers--President, Vice President, Secretary/Treasurer--five Members-at-Large will be elected to serve on ACM Council. Please refer to the instructions posted at https://www.esc-vote.com/acm2016. To access the secure voting site, you will need to enter your email address (the email address associated with your ACM member record) and your unique PIN provided by Election Services Co. Please return your ballot in the enclosed envelope, which must be signed by you on the outside in the space provided. The signed ballot envelope may be inserted into a separate envelope for mailing if you prefer this method. All ballots must be received by no later than 16:00 UTC on 24 May 2016. Validation by the Tellers Committee will take place at 14:00 UTC on 26 May 2016. Vicki Hanson is a Distinguished Professor of Computing at Rochester Institute of Technology, U.S. (since 2013), Professor and Chair of Inclusive Technologies, Computing, University of Dundee, U.K. (since 2009), and an IBM Research Staff Member Emeritus (since 2009). Previously, she was Research Staff Member and Manager, IBM T.J. Watson Research Center (1986–2008), Research Associate, Haskins Laboratories, New Haven, CT (1980–86), and Postdoctoral Fellow at the Salk Institute for Biological Studies (1978–80). Vicki is the ACM Vice President. She also currently serves as a member of the ACM Executive Committee and Council, on the ACM-W Europe Executive Committee, and on the ACM Fellows Awards Committee (Chair, 2015). She is Vice President at Large of ACM SIGCHI and an ACM Distinguished Speaker. She has served on the SIG Governing Board Executive Committee (2005–14; SGB Chair 2010–12), and as Chair of SIGACCESS, where she revitalized the SIG and established a successful annual conference (ASSETS). She co-founded the field's premier archival journal (ACM Transactions on Accessible Computing) and served as Associate Editor of ACM TWEB. She was on the organizing committee for several SIGPLAN OOPSLA conferences, chaired the recent ACM CEO Search Committee, and currently serves on the Royal Society of Edinburgh Fellows committee (since 2013; Convener 2015). She is an ACM Fellow, a Chartered Fellow of the British Computer Society, a Fellow of the Royal Society of Edinburgh, and a Senior Member of IEEE.

An underlying assumption in conventional multi-view learning algorithms is that all views can be simultaneously accessed. However, due to various factors when collecting and pre-processing data from different views, the streaming view setting, in which views arrive in a streaming manner, is becoming more common. By assuming that the subspaces of a multi-view model trained over past views are stable, here we fine tune their combination weights such that the well-trained multi-view model is compatible with new views. This largely overcomes the burden of learning new view functions and updating past view functions. We theoretically examine convergence issues and the influence of streaming views in the proposed algorithm. Experimental results on real-world datasets suggest that studying the streaming views problem in multi-view learning is significant and that the proposed algorithm can effectively handle streaming views in different applications.

Virtual reality and artificial intelligence (AI) are becoming powerful tools needed to revolutionize education. Experts suggest the use of technology, with the integration of the ever-evolving cyber tools, will unify education and research environment and network. Despite the threat of artificial intelligence to rise up against humans and destroy humanity within decades, AI continues to prove its usefulness to mankind. Recently, artificial intelligence makes headlines for having a potential to provide solutions to various global issues such as poaching, illegal logging, cyber-\attacks, in aiding cancer diagnosis and in education. The rise of technology has changed the way students communicate and entertain themselves.

Startup Zero Zero Robotics just took the wraps off its eye in the sky, the Hover Camera. The company hasn't set a price but expects the lightweight drone (it weighs in at 240 grams) to cost under US 600. The flying camera is a relatively new type of gadget. It all started about a year ago, when startup Lily Camera came out of stealth with its 500 to 1000 camera drone and argued that it wasn't so much a drone as a simple-to-use flying camera. This March, drone-maker DJI introduced the Phantom 4, with autonomous flying and tracking features that essentially make it that company's first flying camera at 1400.

ADELPHI, MD - FEBRUARY 04: (AFP OUT) U.S. President Barack Obama tours a seventh grade classroom that uses technology to enhance students' learning experience, prior to delivering remarks on the ConnectED Initiative at Buck Lodge Middle School February 4, 2014 in Adelphi, Maryland. Virtual reality and artificial intelligence (AI) are becoming powerful tools needed to revolutionize education. Experts suggest the use of technology, with the integration of the ever-evolving cyber tools, will unify education and research environment and network. Despite the threat of artificial intelligence to rise up against humans and destroy humanity within decades, AI continues to prove its usefulness to mankind. Recently, artificial intelligence makes headlines for having a potential to provide solutions to various global issues such as poaching, illegal logging, cyber-\attacks, in aiding cancer diagnosis and in education.

Startup Zero Zero Robotics just took the wraps off its eye in the sky, the Hover Camera. The company hasn't set a price but expects the lightweight drone (it weighs in at 240 grams) to cost under US 600. The flying camera is a relatively new type of gadget. It all started about a year ago, when startup Lily Camera came out of stealth with its 500 to 1000 camera drone and argued that it wasn't so much a drone as a simple-to-use flying camera. This March, drone-maker DJI introduced the Phantom 4, with autonomous flying and tracking features that essentially make it that company's first flying camera at 1400.

Machine Learning for Data Science and Analytics is a free, self-paced online course conducted by the Columbia University. This course helps you learn the principles of machine learning and the importance of algorithms. Machine Learning is a growing field that is used when searching the web, placing ads, credit scoring, stock trading and for many other applications. This data science course is an introduction to machine learning and algorithms. You will develop a basic understanding of the principles of machine learning and derive practical solutions using predictive analytics.

For anyone that hasn't yet joined the Becoming a Data Scientist Podcast Data Science Learning Club, I thought I'd write up a summary of what we've been doing! The first activity involved setting up a development environment. Some people are using R, some using python, and there are several different development tools represented. In this thread, several people posted what setup they were using. I posted a "hello world" program and the code to output the package versions.