During the last two years, Microsoft has upped the ante on Machine Learning and Analytics. From hiring top notch data scientists to acquiring niche startups, Redmond has made the all the right moves to transform Azure into one of the best analytics platforms. These investments have started to pay off for the company. It has been successful in articulating and demonstrating the value of data-driven insights to governments, medical institutions, and public sector organizations. Emerging markets that are turning technology savvy are becoming the hotbed for evaluating the upcoming trends such as Machine Learning and Artificial Intelligence.

From May to July 2016, over one thousand Kagglers competed in Facebook's fifth recruitment competition: Predicting Check-Ins. In this challenge, Kagglers were required to predict the most probable check-in locations occurring in artificial time and space. As the first place winner, Tom Van de Wiele, notes in this winner's interview, the uniquely designed test dataset contained about one trillion place-observation combinations, posing a huge difficulty to competitors. Tom describes how he quickly rocketed from his first getting started competition on Kaggle to first place in Facebook V through his remarkable insight into data consisting only of x,y coordinates, time, and accuracy using k-nearest neighbors and XGBoost. I have completed two Master programs at two different Belgian universities (Leuven and Ghent), one in Computer Science (2010) and one in Statistics (2016).

In this example we are going to look at a classification analysis of eye movement patterns. Although complex preprocessing steps can be performed to extract higher-order features from the raw coordinate timeseries provided by an eye-tracker, we are keeping it simple. It contains coordinate timeseries of 144 trials (recorded with 350 Hz), where subjects either looked at upright or inverted images of human faces. Each timeseries snippet covers 3 seconds. This data has been pre-processed to remove eyeblink artefacts.

The technologies on Gartner Inc.'s Hype Cycle for Emerging Technologies, 2016 reveal three distinct technology trends that are poised to be of the highest priority for organizations facing rapidly accelerating digital business innovation. Transparently immersive experiences, the perceptual smart machine age, and the platform revolution are the three overarching technology trends that profoundly create new experiences with unrivaled intelligence and offer platforms that allow organizations to connect with new business ecosystems. The Hype Cycle for Emerging Technologies report is the longest-running annual Gartner Hype Cycle, providing a cross-industry perspective on the technologies and trends that business strategists, chief innovation officers, R&D leaders, entrepreneurs, global market developers and emerging-technology teams should consider in developing emerging-technology portfolios. "The Hype Cycle for Emerging Technologies is unique among most Hype Cycles because it distills insights from more than 2,000 technologies into a succinct set of must-know emerging technologies and trends that will have the single greatest impact on an organization's strategic planning," said Mike J. Walker, research director at Gartner. "This Hype Cycle specifically focuses on the set of technologies that is showing promise in delivering a high degree of competitive advantage over the next five to 10 years."

Which authors of this paper are endorsers? Disable MathJax (What is MathJax?)

As machines become more intelligent, they become embedded in countless facets of life. In some ways, they can act almost as full-fledged members in human-machine teams. In such cases, as with any team, trust is a necessary ingredient for good performance. But the dynamics of trust between people and machines are not yet well-understood. With a two-year project funded through the SUTD-MIT Postdoctoral Fellows Program, a collaboration between MIT and the Singapore University of Technology and Design (SUTD), postdoc Xi Jessie Yang, MIT Department of Aeronautics and Astronautics Assistant Professor Julie Shah, and SUTD Engineering Product Development Professor Katja Hölttä-Otto aim to develop greater knowledge in this area.

With the rapid growth of the Internet of Things (IoT), tens of billions of sensor devices are projected to connect in the next decade. These connected sensor devices will automate processes across a broad range of economic sectors, from industrial plants to healthcare management, delivering productivity gains and hopefully quality-of-life improvements.

So, how do we overcome "notification overload" in healthcare? We need the right kind of tools. We need tools that can automate the complex interdisciplinary workflows that result in much of the notification burden. AI-assisted care plan creation, sharing platforms to involve all stakeholders (physicians, home health agencies, care coordinator nurses, patients, and health plans), are a part of the answer. Regulatory and policy changes (within institutions and within health plans) will be needed to facilitate this, once the tools are available.

X.ai is an NYC based artificial intelligence company that's raised over 30 million. I sat down with the founder Dennis Mortensen to learn more about how they're positioning and selling the product to the enterprise. Talking to him got me super curious about the rise of artificial intelligence, and I hope this interview does similar for you. SUBSCRIBE for more videos like this: http://youtube.com/alxberman?sub_conf... Need lead generation or marketing support for your agency?

Bell started working at Intel in 1998. She brought her anthropological research and fieldwork techniques to the world of microprocessors, wearables and artificial intelligence. Over the years, her formal role has evolved from director of user experience at Intel's research lab to VP of corporate strategy. But regardless of the titles, her work has remained firmly focused on studying the patterns and complexities of human behavior across cultures. In her self-proclaimed role as a "full-time anthropologist and part-time futurist," she examines the meaning of "intelligence" within the context of machines, while she continues to trace its cultural impact on humans and their relationships. At a time when robotic helpers and virtual assistants are starting to infiltrate our personal lives, the need to assess the implications of this new kind of interaction feels more pertinent than ever. I recently called Bell to talk about the social impact of building relationships with our machines and the ways in which the story of AI is deeply connected to the history of human culture. In what ways does the study of human societies and cultures drive technological innovation? And how does that translate into your work at Intel?