Alibaba Group Holding Ltd. Chairman Jack Ma said society should prepare for decades of pain as the internet disrupts the economy. The world must change education systems and establish how to work with robots to help soften the blow caused by automation and the internet economy, Ma said in a speech to an entrepreneurship conference in Zhengzhou, China. "In the next 30 years, the world will see much more pain than happiness," Ma said of job disruptions caused by the internet. "Social conflicts in the next three decades will have an impact on all sorts of industries and walks of life." It was an unusual speech for the Alibaba co-founder, who tends to embrace his role as visionary and extol the promise of the future.

When robot Nao laughs, he does so with his whole body: slapping his knees, shaking his head. But the adorable android, made by SoftBank Robotics, is not merely good at expressing mirth; he can correctly identify as much as 65 percent of happy laughter outbursts in humans, according to a study presented in 2015 at a nonverbal language workshop in the Netherlands. Once robots like Nao master human laughter, they will make far more likable and realistic companions. Nao's creators and other scientists are studying the minutiae of human laughter--acoustics, breath, body movements and vibrations--to translate them into algorithms that robots and avatars can learn. And that includes learning how to be funny. In 2016 researchers in South Korea and Singapore showed that Nao is already quite good at telling jokes.

We consider forecasting a single time series using high-dimensional predictors in the presence of a possible nonlinear forecast function. The sufficient forecasting (Fan et al., 2016) used sliced inverse regression to estimate lower-dimensional sufficient indices for nonparametric forecasting using factor models. However, Fan et al. (2016) is fundamentally limited to the inverse first-moment method, by assuming the restricted fixed number of factors, linearity condition for factors, and monotone effect of factors on the response. In this work, we study the inverse second-moment method using directional regression and the inverse third-moment method to extend the methodology and applicability of the sufficient forecasting. As the number of factors diverges with the dimension of predictors, the proposed method relaxes the distributional assumption of the predictor and enhances the capability of capturing the non-monotone effect of factors on the response. We not only provide a high-dimensional analysis of inverse moment methods such as exhaustiveness and rate of convergence, but also prove their model selection consistency. The power of our proposed methods is demonstrated in both simulation studies and an empirical study of forecasting monthly macroeconomic data from Q1 1959 to Q1 2016. During our theoretical development, we prove an invariance result for inverse moment methods, which make a separate contribution to the sufficient dimension reduction.

As the emergence and the thriving development of social networks, a huge number of short texts are accumulated and need to be processed. Inferring latent topics of collected short texts is useful for understanding its hidden structure and predicting new contents. Unlike conventional topic models such as latent Dirichlet allocation (LDA), a biterm topic model (BTM) was recently proposed for short texts to overcome the sparseness of document-level word co-occurrences by directly modeling the generation process of word pairs. Stochastic inference algorithms based on collapsed Gibbs sampling (CGS) and collapsed variational inference have been proposed for BTM. However, they either require large computational complexity, or rely on very crude estimation. In this work, we develop a stochastic divergence minimization inference algorithm for BTM to estimate latent topics more accurately in a scalable way. Experiments demonstrate the superiority of our proposed algorithm compared with existing inference algorithms.

Naoki Nagai, a 36-year-old Harvard graduate who grew up in Japan, is a one-man hedge fund. For the past 16 months he has written hundreds of algorithms in much the same manner as quantitative traders in the City of London or Wall Street. But, rather than trade from a Canary Wharf skyscraper or a Manhattan boutique fund, he does so from his home in Honolulu. In August 2006, Nagai left his job as a management consultant in Tokyo to establish a translation company, which over the next few years began to thrive. The success of his organisation, and the fact it wasn't dependent on location, gave Nagai the opportunity to reconsider his lifestyle. He chose to move from Japan to Hawaii. With its appealing climate and laid-back lifestyle, Honolulu seemed a great place to raise a family. Nagai and his wife arrived in the US in January 2014.

Computer science has long been a discipline seemingly dominated by males, with the number of women in the field, and even of those graduating with technology degrees, perennially lagging behind the number of men. A recent study by the National Girls Collaborative Project in the United States and the success of conferences like "Women in Data" in the UK suggest that this may be beginning to change, and one catalyst for that change may be the burgeoning field of artificial intelligence (AI). Take Cylance, the fastest growing cyber-security software startup in the past ten years, according to research firm Gartner. The company developed an AI-based alternative to traditional antivirus (AV) -- and just recruited the second female member for its fast-growing data scientist team, now numbering 14. Another example of a company embracing women in the field of AI is Fast Forward Labs, an organisation that works with businesses to accelerate their data science and machine intelligence capabilities.

Whenever you spot a trend plotted against time, you would be looking at a time series. The de facto choice for studying financial market performance and weather forecasts, time series are one of the most pervasive analysis techniques because of its inextricable relation to time--we are always interested to foretell the future. One intuitive way to make forecasts would be to refer to recent time points. Today's stock prices would likely be more similar to yesterday's prices than those from five years ago. Hence, we would give more weight to recent than to older prices in predicting today's price. These correlations between past and present values demonstrate temporal dependence, which forms the basis of a popular time series analysis technique called ARIMA (Autoregressive Integrated Moving Average).

MANILA - Filipino business process outsourcing workers are upgrading their skills to prepare for the growing use of artificial intelligence, an industry group said. Call center agents are being trained for higher-paying jobs that require critical thinking, and complex decision-making, Jay Santisteban, operations director of the Contact Center Association of the Philippines (CCAP), told ABS-CBN News. Filipinos are also in a "very good spot" with BPO clients because of their capability to learn and adapt quickly to new situations, Santisteban said. But what we're doing is we're trying to upskill," Santisteban said. In a few years baka maiwanan ang trabaho na repetitive," he said.

Jefferson Graham runs down those 4 wild tech announcements--from the flying boats and cars to drone goggles and Amazon's closet camera, on #TalkingTech LOS ANGELES -- It'll be hard to top this week for wild, crazy technology unveilings. And some may even end up in your hands. How bout: the flying car that looks like a boat, or jet skies maybe, or perhaps a huge drone. The Kitty Hawk Flyer, the personal project from Google co-founder Larry Page, has to top the list of far-out tech product announcements. It's a vehicle that flies -- hot trend this month, by the way -- but stands out for this feature: It only flies over fresh water.

Jefferson Graham runs down those 4 wild tech announcements--from the flying boats and cars to drone goggles and Amazon's closet camera, on #TalkingTech LOS ANGELES -- It'll be hard to top this week for wild, crazy technology unveilings. And some may even end up in your hands. How bout: the flying car that looks like a boat, or jet skies maybe, or perhaps a huge drone? The Kitty Hawk Flyer, the personal project from Google co-founder Larry Page, has to top the list of far-out tech product announcements. It's a vehicle that flies -- hot trend this month, by the way -- but stands out for this feature: It only flies over fresh water.