A former science teacher who believed in the power and possibility of online learning over two decades ago, he taught himself how to build courses in HTML on class intranets. Kevin taught one of the first hybrid, educational technology courses for teachers, for the University of Washington. And, after building countless web pages and classes on the early world wide web, he now helps develop e-learning programs, consults on virtual training'best practices' and has many interests in other internet and educational technology-related areas. Kevin finds he's now enjoying learning more from his children who are all deep into their own technology-related careers and entrepreneurial endeavors. With two new grandchildren, he's investigating more seriously the advancing new technologies in an effort to understand the knowledge and skills necessary to achieve happiness and success in a technological future.

This seminar is part of the Oxford Martin School Hilary Term seminar series: Blurring the lines: the changing dynamics between man and machine Speakers: Dr Carl Frey, James Martin Fellow, Oxford Martin Programme on the Impacts of Future Technology Dr Michael Osborne, University Lecturer in Machine Learning, University of Oxford Will you one day lose your job to a robot, or even an algorithm? Dr Carl Frey and Dr Michael Osborne's recent working paper, 'The Future of Employment: How susceptible are jobs to computerisation?', found that nearly half of US jobs could be susceptible to computerisation over the next two decades. So as technology races ahead, will low-skilled workers need to retrain in order to remain part of the workforce?

Time series modeling is an important problem with many applications in different domains. Here we consider discriminative learning from time series, where we seek to predict an output response variable based on time series input. We develop a method based on convolution kernels to model discriminative learning over streams of text. Our method outperforms competitive baselines in three synthetic and two real datasets, rumour frequency modeling and popularity prediction tasks.

While video becomes more important as a digital media type, video data often remains dark to analytics. This webinar demonstrates how IBM Bluemix OpenWhisk together with Watson services begins to unlock the value of video data. Dark Vision is an application that uploads video files or streams to the cloud, transcodes video data, extracts and passes frames through the Watson Image Recognition and the Alchemy Face Recognition services, and generates meta-data to use in categorizing the video data for searchability. In the presentation, Andreas Nauerz introduces the basics of IBM Bluemix OpenWhisk and Frederic Lavigne demonstrates how to create OpenWhisk code to accomplish Dark Vision's application workflow. Maybe you want to do that because a particular team already has developed skills in this area, maybe because they do mobile development or have done mobile development in the past, and now want to outsource computer-intensive tasks.

The assumption that a college education should take four years is baked into American culture. Colleges in the colonial days were founded on the premise of a four-year degree, a concept imported from Europe. Harvard University experimented with a three-year degree when it was founded in 1636, but the test was short-lived, and the four-year degree has been the standard ever since. We expect students to enter college at 18 and leave when they turn 22, and we worry about those who take a more circuitous route to graduation. But we need to reconsider that long-established, one-size-fits all model.

Today on In Case You Missed It: Ford is testing self-driving cars on a completely dark night course, designed to be used without headlights. An automation company built a flying sphere that can pick up and deliver things with a very sphincter-like gripper system. And Schaft Inc. is showing off its new bipedal robot that can walk on rocky beaches easily. The physicist who is thrilled about his job specializing in snowflakes is a must-watch (post-Zombie fakeout, of course). As always, please share any great tech or science videos you find by using the #ICYMI hashtag on Twitter for @mskerryd.

The 2016 winners were as follows: Tom Dietterich, AAAI President, for AAAI 2017 Awards, please Manuela Veloso, AAAI Past President contact Carol Hamilton at hamilton@aaai.org.

Probabilistic graphical models has been quite a roller coaster over the past few years. Social network analysis is growing less rapidly as well. While the results herein may not come as much surprise, it's fascinating to see the extent to which AI, machine learning, and especially deep learning has proliferated and grown among advanced course offerings. It is incredibly exciting to witness the opportunities for predictive insights & machine intelligence that are affecting every industry and business application, and reassuring that knowledge and understanding of these core areas is only going to increase -- and perhaps become core tools & techniques for an upcoming wave of engineers.

At this point, it's a bit of an open secret that Facebook will announce the arrival of chatbots for Messenger at F8, its annual developer conference. Well, the latest Messenger update all but confirms it. If you were to do a search in the latest version of Facebook's chat app, you'll find a new category heading called "Bots and Businesses." Prior to the update, this would simply read "Businesses," which was a listing of companies that you could message for customer support and general inquiries. Messaging businesses typically involves speaking to a human, however, while talking to chatbots would likely be a more automated experience -- sort of like chatting to the equivalent of a phone tree.

This workshop will attempt to present some of the very recent developments on non-convex analysis and optimization, as reported in diverse research fields: from machine learning and mathematical programming to statistics and theoretical computer science. We believe that this workshop can bring researchers closer, in order to facilitate a discussion regarding why tackling non-convexity is important, where it is found, why non-convex schemes work well in practice and, how we can progress further with interesting research directions and open problems.