Fact is, enterprises have significant legacy voice infrastructure that's costly to replace with pure IP solutions. How can we bring this analog infrastructure into our shiny new cloud applications? There are proven methods to bind both legacy voice applications and traditional PSTN audio into cloud-based applications and services at a carrier scale. In his session at @ThingsExpo, Dan Cunningham, CTO of ReadyTalk, covered real world examples of how enterprises and vendors alike can modernize infrastructure without ditching existing investments. Speaker Bio As CTO of ReadyTalk, Dan Cunningham is responsible for the overall technology strategy of the company as well as management of ReadyTalk's engineering resources.

In this blog post, I provide 10 tips on how our sponsors and exhibitors can maximize their participation at our events. But before reading my top 10 tips for our sponsors and exhibitors, please take a moment and watch this brief Sandy Carter video. "Cloud Expo was really the event to connect with thought leaders, innovators, business folks who are interested in what the cloud can bring to their business. You know really how it allows them to bring the transformation of the business process." Cloud Expo and @ThingsExpo New York and Silicon Valley provide a full year of face-to-face marketing opportunities for your company.

The Schatten-$p$ norm ($00$ satisfying $1/p=1/p_1+1/p_2$, there is an equivalence between the Schatten-$p$ norm of one matrix and the Schatten-$p_1$ and the Schatten-$p_2$ norms of its two factor matrices. We further extend the equivalence to multiple factor matrices and show that all the factor norms can be convex and smooth for any $p>0$. In contrast, the original Schatten-$p$ norm for $0

Multivariate Pattern (MVP) classification can map different cognitive states to the brain tasks. One of the main challenges in MVP analysis is validating the generated results across subjects. However, analyzing multi-subject fMRI data requires accurate functional alignments between neuronal activities of different subjects, which can rapidly increase the performance and robustness of the final results. Hyperalignment (HA) is one of the most effective functional alignment methods, which can be mathematically formulated by the Canonical Correlation Analysis (CCA) methods. Since HA mostly uses the unsupervised CCA techniques, its solution may not be optimized for MVP analysis. By incorporating the idea of Local Discriminant Analysis (LDA) into CCA, this paper proposes Local Discriminant Hyperalignment (LDHA) as a novel supervised HA method, which can provide better functional alignment for MVP analysis. Indeed, the locality is defined based on the stimuli categories in the train-set, where the correlation between all stimuli in the same category will be maximized and the correlation between distinct categories of stimuli approaches to near zero. Experimental studies on multi-subject MVP analysis confirm that the LDHA method achieves superior performance to other state-of-the-art HA algorithms.

With the development of community based question answering (Q&A) services, a large scale of Q&A archives have been accumulated and are an important information and knowledge resource on the web. Question and answer matching has been attached much importance to for its ability to reuse knowledge stored in these systems: it can be useful in enhancing user experience with recurrent questions. In this paper, we try to improve the matching accuracy by overcoming the lexical gap between question and answer pairs. A Word Embedding based Correlation (WEC) model is proposed by integrating advantages of both the translation model and word embedding, given a random pair of words, WEC can score their co-occurrence probability in Q&A pairs and it can also leverage the continuity and smoothness of continuous space word representation to deal with new pairs of words that are rare in the training parallel text. An experimental study on Yahoo! Answers dataset and Baidu Zhidao dataset shows this new method's promising potential.

Arrival Amy Adams stars in this elegant, involving science fiction drama that is simultaneously old and new, revisiting many alien invasion conventions but with unexpected intelligence, visual style and heart. Best Worst Thing That Ever Could Have Happened This superb documentary directed by Lonny Price covers a rich swath of emotional and creative ground as it tracks the unexpected failure of theater gods Stephen Sondheim and Hal Prince's hugely anticipated 1981 Broadway collaboration "Merrily We Roll Along." The Eagle Huntress A portrait of a 13-year-old Kazakh girl from Mongolia who defies eons of tradition by learning to hunt with fierce golden eagles is a documentary so satisfying it makes you feel good about feeling good. The Edge of Seventeen Hailee Steinfeld gives a superb performance as a high-school misfit in Kelly Fremon Craig's disarmingly smart teen dramedy, the rare coming-of-age picture that feels less like a retread than a renewal. Elle Paul Verhoeven's brilliantly booby-trapped new thriller starring Isabelle Huppert is a gripping whodunit, a tour de force of psychological suspense and a wickedly droll comedy of manners.

In a way, AI is about understanding, and then mimicking how we think, learn and process information. The science and applications of AI have evolved since the early years: 1950's 1980's 2010's Generation 1 (From 1950's): Rule Based Systems (No Learning) In the early days, most applications of AI were rule-based computer programs (commonly known as Expert Systems) designed to solve problems that human brains performed easily. Such AI programs required experts to develop rules and combine with programs to solve problems. It required a programmer to write a program to capture the knowledge of a subject matter expert. The program then asked a series of questions to a user (usually not an expert in that subject) and then based on the answers/input provided, the computer would suggest a "solution" to the problem.

Natural disasters are out of the reach and influence of human beings. However, a lot can be done to minimize loss of lives. Artificial intelligence is one viable option that can potentially prevent massive loss of lives while at the same time make rescue efforts easy and efficient. To learn more, checkout the infographic below created by Eastern Kentucky University's Online Masters in Safety degree program. In the period between 2005 and 2015, a total of 242 natural disasters occurred in the United States of America.

Notman House is a local ICT mecca in Montreal. Google's $3.4 million investment in the Montreal Institute for Learning Algorithms (MILA) and new lab opening in The City of Saints not only highlights the company's banking on artificial intelligence, but its faith in Canada's ICT industries to help it in that quest. Montreal is running neck and neck with Toronto and Vancouver to attract talent and incubate businesses. Though Ontario holds a lead over it, Montreal remains, "the second most popular location for most types of ICT jobs" after Toronto according to the Canadian Information and Communications Technology Council, and over 222,000 people are employed across various industries, from gaming to AI R&D. The lab will be led by University of Montreal and Twitter alumnus Hugo Larochelle, whose like-minded associates at MILA are already heavily invested in deep learning applications.

In September, Apple quietly acquired Tuplejump, a little-known Hyderabad-based startup. Tuplejump is an Artificial Intelligence (AI) company that helps clients store, process and visualise data. In simple terms, it helps, say, an e-commerce player to use all the data it collects to improve conversion rates--the number of people who end up buying something out of the total number of visitors. This was Apple's first acquisition in India and the third one this year of an AI company. India-based AI startups are hardly visible and don't command eyepopping valuations that e-commerce companies do.