And now the original developers behind Siri will be working under Samsung. An intelligent and powerful assistant integrated into Samsung's array of gadgets – Gear S watches, Galaxy smartphones, Smart TVs, and more – would help the South Korean firm against increased competition from the Google Assistant, Apple's Siri and Amazon's Alexa. The acquisition of Viv Labs would also allow Samsung to reduce its dependence on Google services. Samsung has already launched its own contactless payment options – Samsung Pay – which directly competes with Google's Android Pay solution.

In this latest University of Sydney'Open for Discussion' episode our host Dr Chris Neff speaks with Dr Michael Harre, lecturer in Complex Systems in the Faculty of Engineering and Information Technologies and artificial intelligence aficionado about where AI really is and how it is affecting our lives. Michael Harre will be appearing at Raise the Bar, Tuesday 18th October. Chris Neff: Welcome to Open for Discussion. Joining me today is Dr Michael Harre from the University's Faculty of Engineering and Information Technologies. Michael is an artificial intelligence aficionado, try saying that 3 times fast, and lecturer in complex systems. Chris Neff: Can I ask first, what is artificial intelligence and secondly, what got you into artificial intelligence? What was your background, how did you come to this? Ahh.. There's no straight forward answer in the sort of...general definition but usually it's something that runs on a computer that;s trying to do something kinda human like but perhaps not being very..very good at it. Because my understanding is mostly a star trek, star wars aahhhh... Will Smith movies and other kind of.. Dr Michael Harre: Ah yeah there's some great movies out there and the movies out there umm..they portray a combination of robot and ah..robots with some form of human like intelligence but umm..what you see in the robots is a bit more like um..what we think of as human behaviour and sort of expressing our human mind ah..but that's not what we are able to do at all with artificial intelligence yet.

If there's one thing doctors and patients want from breast cancer diagnoses, it's reliability. Keeping up with the massive flow of research data on breast cancer is a challenge for scientists. And the variety of methods used to analyze that data make reliable predictions difficult to come by. A team from Harvard Medical School's Beth Israel Deaconess Medical Center (BIDMC) tackled this issue using deep learning, in the 2016 Camelyon Grand Challenge. Hosted by the International Symposium on Biomedical Imaging, the competition aims to determine how algorithms can help pathologists better identify cancer in lymph node images.

When writing the screenplay for 1968's 2001, Arthur C. Clarke and Stanley Kubrick were confident that something resembling the sentient, humanlike HAL 9000 computer would be possible by the film's namesake year. That's because the leading AI experts of the time were equally confident. Clarke and Kubrick took the scientific community's predictions to their logical conclusion, that an AI could have not only human charm but human frailty as well: HAL goes mad and starts offing the crew. But HAL was put in an impossible situation, forced to hide critical information from its (his?) coworkers and ordered to complete the mission to Jupiter no matter what. "I'm afraid, Dave," says the robot as it's being dismantled by the surviving astronaut.

Rumors about the upcoming Galaxy S8 have been swirling for months, but the latest teaser comes from Samsung themselves. The South Korean electronics company just announced the acquisition of Viv, an artificial intelligence platform from the creators of Siri. Google recently debuted its new Pixel phone with Google Assistant. Artificial intelligence that can help users with daily tasks and more. The new iPhone 7 has a smarter more advanced Siri too. Samsung is lacking in this area, but is poised to make a big entrance potentially starting with the Galaxy S8.

This column provides an encounter with the Artificial Intelligence research community in the state of Israel. The first section introduces this community and its special attributes. The second section provides overview on some recent research projects done in Israel. The author serves as the chair of the Israeli AI association

The conference The goal of the AAAI-17 Student evening poster programs, and location is a great starting Abstract and Poster program is to provide will have a short paper included in the point to explore the City's tremendous a forum in which students can proceedings. Submissions from everyone, ethnic and cultural diversity and its present and discuss their work during including authors of paper submissions wide variety of offerings. San Francisco its early stages, meet some of their to AAAI, IAAI, and AAAI-17 is also perfectly positioned to explore peers who have related interests, and workshops, are encouraged. Work submitted the entire Bay Area, whether for recreation introduce themselves to more senior to other tracks (such as the or business.

Rank aggregation systems collect ordinal preferences from individuals to produce a global ranking that represents the social preference. Rank-breaking is a common practice to reduce the computational complexity of learning the global ranking. The individual preferences are broken into pairwise comparisons and applied to efficient algorithms tailored for independent paired comparisons. However, due to the ignored dependencies in the data, naive rank-breaking approaches can result in inconsistent estimates. The key idea to produce accurate and consistent estimates is to treat the pairwise comparisons unequally, depending on the topology of the collected data. In this paper, we provide the optimal rank-breaking estimator, which not only achieves consistency but also achieves the best error bound. This allows us to characterize the fundamental tradeoff between accuracy and complexity. Further, the analysis identifies how the accuracy depends on the spectral gap of a corresponding comparison graph.

Commonly used in computer vision and other applications, robust PCA represents an algorithmic attempt to reduce the sensitivity of classical PCA to outliers. The basic idea is to learn a decomposition of some data matrix of interest into low rank and sparse components, the latter representing unwanted outliers. Although the resulting optimization problem is typically NP-hard, convex relaxations provide a computationally-expedient alternative with theoretical support. However, in practical regimes performance guarantees break down and a variety of non-convex alternatives, including Bayesian-inspired models, have been proposed to boost estimation quality. Unfortunately though, without additional a priori knowledge none of these methods can significantly expand the critical operational range such that exact principal subspace recovery is possible. Into this mix we propose a novel pseudo-Bayesian algorithm that explicitly compensates for design weaknesses in many existing non-convex approaches leading to state-of-the-art performance with a sound analytical foundation. Surprisingly, our algorithm can even outperform convex matrix completion despite the fact that the latter is provided with perfect knowledge of which entries are not corrupted.

It knew enough about medical diagnoses and literature to beat "Jeopardy!" Now, an IBMcomputer platform called Watson is taking on something really tough: teaching third-grade math. For the past two years, the IBM Foundation has worked with teachers and their union, the American Federation of Teachers, to build Teacher Advisor, a program that uses artificial-intelligence technology to answer questions from educators and help them build personalized lesson plans. By the end of the year, it will be available free to third-grade math teachers across the country and will add subject areas and grade levels over time. "The idea was to build a personal adviser, so a teacher would be able to find the best lesson and then customize the lesson based upon their classroom needs," said Stanley S. Litow, president of the IBM Foundation. "By loading a massive amount of content, of teaching strategies, lesson plans, you'd actually make Watson the teacher coach," Mr. Litow said.