Smartphone apps can now recognize faces in photos and translate from one language to another. Take Facebook as an example--using A.I. to fight troublemakers. Weeding out false news may also become a reality, thanks to machine learning algorithms. Then there are those who think China is positioning itself to dominate the A.I. age. Others point out, though, that the U.S. has a "30-year head start" in A.I. development.

Machine Learning will come to change the way you work, earn a livelihood, purchase and consume goods and services. Nearly every working professional and entrepreneur who keeps a finger on the pulse of the market would have heard or read the words'machine learning' by now. For many of them, trailblazing pioneers at the forefront of new technologies, like Steve Jobs and Elon Musk, have become universal role models. What one needs to realise is that what the personal computer and the smartphone were to Steve Jobs, machine learning (ML) could be for you – but you need to start now. Technology is already entering the market at a rapid pace, and the opportunities in this field are growing at an exponential rate.

In the natural world, many species can walk over slopes and irregular surfaces, reaching places inaccessible even to the most advanced rover robots. It remains a mystery how complex movements are handled so seamlessly by even the tiniest creatures. What we do know is that even the simplest brains contain pattern-generator circuits (CPGs)[1], which are wired up specifically for generating walking patterns. Attempts to replicate such circuits artificially have so far had limited success, due poor flexibility. Now, researchers in Japan and Italy propose a new approach to walking pattern generation, based on a hierarchical network of electronic oscillators arranged over two levels, which they have demonstrated using an ant-like hexapod robot.

Senior isolation is becoming a major social problem in Japan, as a super-aged society where more than a quarter of population is over 65 years old. Many elderly people are living in single-resident homes without family or social support. Even in nursing home, residents stay in their private bedrooms lonely without participating social activities, such as chatting, playing game, watching TV together at a living room, etc. Since social isolation leads to serious consequences such as disuse syndrome, mental depression, suicide etc., main-taining person’s sense of community is very important. But measuring sense of community is difficult because it is a mental process and many kinds of activities and interactions are involved in the process. In this paper, we define Social Activities of Daily Living (SADL) to focus on social activities to enhance the sense of community. We also propose a multimodal sensor based recognition method for SADL, which is implemented in the IoT-based emotion recognition robot for nursing environment. The robot monitors the daily activities and emotions of the residents, estimates the social relationships of the residents, takes care of the residents who are isolated from the community, and reduces their loneliness feelings by forming a good relationship in community.

The prevalence of online media has attracted researchers from various domains to explore human behavior and make interesting predictions. In this research, we leverage heterogeneous social media data collected from various online platforms to predict Taiwan's 2016 presidential election. In contrast to most existing research, we take a "signal" view of heterogeneous information and adopt the Kalman filter to fuse multiple signals into daily vote predictions for the candidates. We also consider events that influenced the election in a quantitative manner based on the so-called event study model that originated in the field of financial research. We obtained the following interesting findings. First, public opinions in online media dominate traditional polls in Taiwan election prediction in terms of both predictive power and timeliness. But offline polls can still function on alleviating the sample bias of online opinions. Second, although online signals converge as election day approaches, the simple Facebook "Like" is consistently the strongest indicator of the election result. Third, most influential events have a strong connection to cross-strait relations, and the Chou Tzu-yu flag incident followed by the apology video one day before the election increased the vote share of Tsai Ing-Wen by 3.66%. This research justifies the predictive power of online media in politics and the advantages of information fusion. The combined use of the Kalman filter and the event study method contributes to the data-driven political analytics paradigm for both prediction and attribution purposes.

Knowledge Graph Embedding methods aim at representing entities and relations in a knowledge base as points or vectors in a continuous vector space. Several approaches using embeddings have shown promising results on tasks such as link prediction, entity recommendation, question answering, and triplet classification. However, only a few methods can compute low-dimensional embeddings of very large knowledge bases. In this paper, we propose KG2Vec, a novel approach to Knowledge Graph Embedding based on the skip-gram model. Instead of using a predefined scoring function, we learn it relying on Long Short-Term Memories. We evaluated the goodness of our embeddings on knowledge graph completion and show that KG2Vec is comparable to the quality of the scalable state-of-the-art approaches and can process large graphs by parsing more than a hundred million triples in less than 6 hours on common hardware.

Chinese scientists have developed a robot that could be straight out of the Iron Man movies. The two-legged bot is outfitted with small jet engines that are attached to its feet. Robotics engineers at Guangdong University of Tech's School of Automation in China strapped two duct fans to the robot's feet which allow it to cross wider distances than it would have been able to previously. Robotics engineers at Guangdong University of Tech's School of Automation in China developed a bipedal robot that can cross wide distances, thank to two small jet engines It also solves a major problem commonly experienced by robot developers. Most bipedal robots are only capable of making static movements like walking forward in short, controlled steps.

Cortana is the AI-powered digital assistant that has one of its homes in Windows 10. It can do various tasks such as opening apps, doing simple math, suggest discount coupons, etc. But an Israel-based researcher duo, Tal Be'ery and Amichai Shulman, have discovered another thing Cortana can do. It can provide hackers a way to hack a Windows 10 PC, even if it's locked. Locking your PC is fundamental to preventing others from accessing it when you leave it unattended.

In China, officials and companies have deployed facial-recognition technology to a degree uncommon elsewhere, both commercially and--more controversially--for widespread surveillance. The government of the southwestern Guizhou province, Tsinghua University, and Beijing-based d-Ear Technologies announced they are collaborating on a pilot project that will link unique voice features to people's national ID information and create, maintain, and secure a database of "voiceprints." China's digitally-connected population has enabled the government to track people in many forms, such as using facial recognition to prevent toilet paper theft and jaywalking. But d-Ear (link in Chinese) and other companies say that voice recognition is a better and cheaper way to verify identity. Cheng Ge, marketing director of d-Ear, founded in 2002, told Quartz this week that the d-Ear pilot would be similar to social media giant Tencent's December pilot program in the southern city of Guangzhou, which allowed people to use facial recognition within its all-purpose WeChat app to create a digital version of their government-issued ID card.

You return home to your penthouse apartment after a long day at work auctioning Cryptokitties and other cryptogoods on a peer-to-peer marketplace. You grab a bottle of tangerine-flavored weed soda from the fridge and sink into your couch. A wooden side table, custom-built by a robot in India, holds a box containing your antidepressant patches. You peel off the back and slap one on your arm. The television replies in the warm, fully human-sounding female whisper you chose for it: "We've got five new videos from your favorite ASMR channels.