Unlike Consumer IoT, Industrial IoT (IIoT) is applied to manufacturing and supply chain environment, the under development segment in IoT segment. IIoT is expected to create vivid impact across the ecosystem players and industry verticals like governments, city infrastructure, aviation, power generation, transportation and many more. Without any doubt IIoT is going to create real market opportunity for IoT. The inherent journey began during the era of Industry 1.0 when mechanization of production system revolutionizes the world and real race of industrialization starts. Since then industries went through several innovations and upgradation such as mass production, assembly line, division of labor, electricity, automation of production process, and integration with IT system throughout the journey of Industry 2.0 and Industry 3.0. The emergence of robust internet connectivity & network, IoT technologies, industrial robotics, cloud based technologies, and intelligent machines pushed the whole concept of industry into a new shape called Industry 4.0, the fourth industrial revolution.

Despite plans to invest in machines and artificial intelligence as part of their strategy to boost productivity, many automotive and industrial equipment companies are failing to implement the measures needed to harness these capabilities, according to a new report from Accenture. The report, "Machine dreams: Making the Most of the Connected Industrial Workforce," is based on interviews with more than 500 business executives in Asia, Europe and the United States involved in setting their company's strategy for the connected industrial workforce. According to the report, manufacturing and production are undergoing rapid change as machines and AI are becoming closely integrated with personnel, creating the connected industrial workforce. By combining mobile, safety and tracking technologies with analytics, companies are enhancing the activities of an industrial worker. The report concludes that the creation of a connected industrial workforce is already part of the business strategy of the majority of automotive and industrial equipment producers, cited by 94 percent of respondents.

Mainland Chinese start-up Horizon Robotics, founded by the former head of online search giant Baidu's Institute of Deep Learning, claims it is on pace to bring chips with built-in artificial intelligence (AI) technology to market. "General processors are too slow for AI functions. A dedicated chip will dramatically increase the speed of these functions," Yu Kai, the founder and chief executive of Horizon Robotics told the South China Morning Post. Founded in Beijing in July, Horizon Robotics is developing chips and software that attempt to mimic how the human brain solves abstract tasks, such as voice and image recognition, that are difficult for regular computer programmes. It also makes sensors for smart devices.

A car's driver doesn't necessarily have to be human: The artificial intelligence behind Google Inc.'s self-driving system could count, according to federal highway safety officials. In a letter posted on the National Highway Traffic Safety Administration's website, the agency responded to Google's request for interpretation of several federal safety standards as they apply to the tech giant's self-driving cars. As a premise of the interpretation, "NHTSA will interpret'driver' in the context of Google's described motor vehicle design as referring to the [self-driving system], and not to any of the vehicle occupants," Chief Counsel Paul Hemmersbaugh said in the letter. "We agree with Google its [self-driving vehicle] will not have a driver in the traditional sense that vehicles have had drivers during the last more than 100 years." Google's not-so-secret special projects lab, Google X, is housed in an old shopping mall near Mountain View, Calif.

Each week has some assigned Coursera videos. The quiz on those videos is due by 11:59pm on Monday of that week. Since the in-class meetings build on the material in the Coursera videos, it is important that you watch them before class. No lectures, tutorials, or office hours will be held for the duration of the CUPE 3902 Unit 1 strike. You should have received an e-mail with further details.

Customers are becoming "impatient narcissists," according to Rick Davidson, president and CEO of the consultancy Cimphoni. "They want what they want, and they want it now," he said during this presentation on cognitive computing for the enterprise at the recent Fusion CEO-CIO Symposium in Madison, Wis. Today's technology-connected customers care about wait times, ease of use and responsiveness. The deeper the technology is integrated into their lives, the more they'll expect from the companies they do business with, Davidson warned. CIOs should begin to consider the machine learning and artificial intelligence (AI) investments they'll likely have to make to meet evolving customer expectations.

In previous articles, we've talked about the merits of artificial intelligence and big data and how these technologies can enable a multitude of industries to begin learning how to do things more effectively. One area where these technologies can be used is in digital marketing. Also referred to as "programmatic marketing", AI and big data can be used to figure out what digital ad to serve you up at any given time to increase the likelihood that you'll click on it. While we've said before that you can't invest in artificial intelligence yet as a retail investor, we did come across one publicly traded company called Rocket Fuel (NASDAQ:FUEL) which is playing in the "programmatic marketing" space and while their value proposition sounds exciting, there's much more to this company than meets the eye. Founded in 2008, Rocket Fuel uses artificial intelligence and big data to determine which ad is best to serve at any given moment in order to increase the likelihood of you clicking on that ad, and then engaging with the advertiser.

It's a notion marketers will drool over: Imagine if their overloaded job responsibilities could be wiped clean by the use of robots to do tedious marketing tasks for them. Just as we already use programmatic buying and other data-driven marketing tools to simplify difficult and time-consuming processes, artificial intelligence (AI) is viewed by both robotics experts and marketing professionals as a tool to expedite menial content creation in the future. Efforts to bring AI to the mainstream are underway. IBM's Watson AI is already making appearances in ads holding conversations with celebrities. Robotic writing solutions have been used for simple writing tasks, such as recapping sporting events.

I'm often asked about my thoughts on the future. What will transportation be like? What new forms of entertainment will we enjoy? While I have covered these topics in previous articles, it's important to understand that they're all forms of work. So today I want to discuss the future of work -- how technological advancements, namely robotic assistants and tools, as well as tech-enhanced globalization, will affect our daily work flow and the labor market in general.

Human patrols serve as the most direct form of protection of endangered animals, especially in large national parks. However, protection agencies have limited resources for patrols. With support from the National Science Foundation (NSF) and the Army Research Office, researchers are using artificial intelligence (AI) and game theory to solve poaching, illegal logging and other problems worldwide, in collaboration with researchers and conservationists in the U.S., Singapore, Netherlands and Malaysia. "In most parks, ranger patrols are poorly planned, reactive rather than pro-active, and habitual," according to Fei Fang, a Ph.D. candidate in the computer science department at the University of Southern California (USC). Fang is part of an NSF-funded team at USC led by Milind Tambe, professor of computer science and industrial and systems engineering and director of the Teamcore Research Group on Agents and Multiagent Systems.