There is a tendency to see artificial intelligence as the latest technology fad, either a buzzword that canny entrepreneurs exploit or the starting point for dystopian nightmares. Both are potentially accurate descriptions of much of the discussion surrounding AI, but both miss the most important point: AI is almost certain to become the most critical feature of the digital economy, assuming a role akin to electricity in the industrial revolution. If that prediction is correct -- and few disagree -- then mastery of AI and leadership in the field could determine the future economic and military balance of power. AI is shorthand for an amalgam of computer processes that permit machines to evaluate and learn about their environment on their own. It includes automated intelligence, assisted intelligence, augmented intelligence and autonomous intelligence.

The major factors driving the artificial intelligence in manufacturing market are the increasing usage of robotics in manufacturing, usage of big data technology in the manufacturing sector, computer vision technology being used in manufacturing, and industrial IoT in manufacturing sector. Reluctance among the manufacturers to adopt AI-Based technologies are the major factors that may hinder the progress of the artificial intelligence in Manufacturing market in the near future. Additionally the growth opportunities of AI-Based technology in emerging and developed countries and more over improving operational efficiency of manufacturing plants are some of the major growth opportunities for the artificial intelligence in Manufacturing market players. Geographically, the artificial intelligence in Manufacturing market has been bifurcated into five regions North America, Europe, Asia Pacific, Middle East & Africa and Latin America. The Artificial Intelligence in Manufacturing market size and forecast period for each region has been estimated from 2017 to 2023.

Visual Investigations 3:28 How a Drone Hunted Three Kurdish Fighters in Syria International 7:15 How Did Bombs Made in Italy Kill a Family In Yemen? International 7:15 How Did Bombs Made in Italy Kill a Family In Yemen? How Did Bombs Made in Italy Kill a Family In Yemen?

A strong declaration from a historically antagonist foe should put chills in the hearts of Americans preparing themselves for the world ahead: Russian President Vladimir Putin says the nation that leads in AI will be the ruler of the world [1]" … The ruler of the world! "The development of artificial intelligence has increasingly become a national security concern in recent years. It is China and the US (not Russia), which are seen as the two frontrunners, with China recently announcing its ambition to become the global leader in AI research by 2030. Many analysts warn that America is in danger of falling behind, especially as the [current US] administration prepares to cut funding for basic science and technology research." Elon Musk, one of America's foremost technology advocates, predicts that countries seeking leadership (and domination) from artificial intelligence will be the basis for World War III[2].

Computers may better predict taxi and ride sharing service demand, paving the way toward smarter, safer and more sustainable cities, according to an international team of researchers. In a study, the researchers used two types of neural networks -- computational systems modeled on the human brain -- that analyzed patterns of taxi demand. This deep learning approach, which lets computers learn on their own, was then able to predict the demand patterns significantly better than current technology. "Ride sharing companies, like Uber in the United States, and Didi Chuxing in China, are becoming more and more popular and have really changed the way people approach transportation," said Jessie Li, associate professor of information sciences and technology, Penn State. "And you can imagine how important it would be to predict the taxi demand because the taxi company could dispatch the cars even before the need arises."

In the classic group testing problem which was first introduced by Dorfman [11], there is a set ofnitems including at most d defective items. The purpose of this problem is to find the defective items with the minimum number of tests. Every test consists of some items and each test is positive if it includes at least one defective item. Otherwise, the test is negative. There are two types of algorithms for the group testing problem, adaptive and non-adaptive. In adaptive algorithm, the outcome of previous tests can be used in the future tests and in non-adaptive algorithm all tests perform simultaneously and the defective items are obtained by considering results of all tests. Regarding some extensions of classical group testing, we can refer to group testing on graphs, complex group testing, additive model, inhibitor model, etc. (see [12, 13, 17] for more information). Aigner [1] proposed the problem of group testing on graphs, in which we look for one defective edge of the given graphGby performing the minimum adaptive tests, where each test is an induced subgraph of the graph G and the test is positive in the case of involving the defective edge.

All countries will feel the impact of automation, but at different speeds and in different ways. In this podcast, McKinsey Global Institute looks at its likely impact in China, Europe, and India. New technologies such as artificial intelligence and automation are reshaping the workplace globally. All countries will feel the impact in some way, shape, or form. In this episode for the McKinsey Global Institute's New World of Work podcast, MGI directors Jonathan Woetzel and Jacques Bughin and MGI partner Anu Madgavkar examine automation's likely impact in China, Europe, and India. I'm Peter Gumbel from the McKinsey Global Institute, and today we'll be taking a look at the quite different ways that new technologies like automation and artificial intelligence will affect work in different parts of the world. Specifically, we'll be looking at China, Europe, and India. These differences come about for a number of reasons that we explain in our new MGI report on the future of work, which is called Jobs lost, jobs gained: Workforce transitions in a time of automation. Among the reasons for these differences are different levels of economic development, different wage rates, and different potential for automation adoption in different economies. First, let's talk about China. Here to do so is Jonathan Woetzel, director of the McKinsey Global Institute, based in Shanghai. Jonathan, perhaps you can start by telling us where the Chinese workforce is at the moment.

China's biggest online commerce company is making big strides in the field of artificial intelligence. The Alibaba Group has developed a machine-learning model which scored higher than human users on the Stanford Question Answering Dataset.

SenseTime Co., a Chinese artificial intelligence start-up backed by Alibaba Holdings Ltd., has formed an alliance with one of the US' top university to jointly explore human and machine intelligence. The Beijing-based firm will jointly work with the Massachusetts Institute of Technology undertake research into original AI technologies such as computer-vision, human-intelligence-inspired algorithms, medical imaging, and robotics, online news outlet QQ Tech reported. SenseTime recently became the first company to join MIT's Intelligence Quest, which aims to leverage the Institute's strengths in brain and cognitive science and computer science to advance research into human and machine intelligence. Considered the world's leading AI unicorn valued at more than USD3 billion, SenseTime has developed a sophisticated proprietary deep learning platform and built applications for multiple industries. The company has offices in Hong Kong, Beijing, Shenzhen, Hangzhou, Shanghai, Chengdu, Kyoto, Tokyo and Singapore.

This is the extract from my presentation done at GECommunity2017 Summit in Kuala Lumpur Malaysia. The summit took place on on 12th and 13th December 2017. This was the biggest summit in Malaysia and opening speech was done by "Sri Haji Mohammad Najib bin Tun Haji Abdul Razak" (Current Prime minister of Malaysia since 2009). If any one is looking for full presentation free copy, please leave your email address in below comment box. I will talk about different elements of PaymentIntelligence (PI) in this post on very high level only.