On the outskirts of Beijing, a policeman peers over his glasses at a driver stopped at a motorway checkpoint. As he looks at the man's face, a tiny camera in one of the lenses of his glasses records his features and checks them with a national database. The artificial intelligence-powered glasses are what Chinese citizens refer to as "black tech", because they spot delinquents on the country's "blacklist". Other examples include robots for crowd control, drones that hover over the country's borders, and intelligent systems to track behaviour online. Some reports claim the government has installed scanners that can forcibly read information from smartphones.

A central task force on Artificial Intelligence (AI) has suggested creating a National Artificial Intelligence Mission (N-AIM) that will serve as a nodal agency for coordinating AI related activities in the country. The report of the task force, set up by the Union Commerce Ministry in August last, has also said "AI should be seen as a scalable problem solver in India rather than only as a booster of economic growth." Professor V Kamakoti, Chairman of the task force and a Professor of IIT, Madras, said the report was a "practical" one and that "all our recommendations have been very pointed and it has been seen to it that they are very much implementable in a short time." According to the report, Artificial Intelligence "is the science and engineering of making intelligent machines, especially intelligent computer programmes." The task force, whose members include those from government and the private sector, besides the academia, has identified 10 domains in India, including Manufacturing, FinTech, Agriculture/Food Processing and Education for implementation of AI.

Key Target audience for Artificial Intelligence in retail is retail solutions, platforms, and service providers, AI system providers. IBM, Google, Microsoft, NVIDIA, Intel, and Amazon Web Services are some of the companies that provide AI in retail products and services. The key vendors profiled in the report are as follows such as IBM (US), Microsoft (US), Amazon Web Services (US), Oracle (US), SAP (Germany), Intel (US), NVIDIA (US), Google (US), Sentient technologies (US), Sales force (US), ViSenze (Singapore). North America is the highest contributor in the adoption and implementation of AI in retail. Artificial intelligence in retail market report provides detailed insights into the global AI in retail market to 2022. North America is expected to have the largest market size during the forecast period.

From eastern Europe to southern Iraq, the U.S. military faces a difficult problem: Adversaries pretending to be something they're not -- think Russia's "little green men" in Ukraine. But a new program from the Defense Advanced Research Projects Agency seeks to apply artificial intelligence to detect and understand how adversaries are using sneaky tactics to create chaos, undermine governments, spread foreign influence and sow discord. This activity, hostile action that falls short of -- but often precedes -- violence, is sometimes referred to as gray zone warfare, the'zone' being a sort of liminal state in between peace and war. The actors that work in it are difficult to identify and their aims hard to predict, by design. "We're looking at the problem from two perspectives: Trying to determine what the adversary is trying to do, his intent; and once we understand that or have a better understanding of it, then identify how he's going to carry out his plans -- what the timing will be, and what actors will be used," said DARPA program manager Fotis Barlos.

The question I always ask myself, just like any human being, is who am I and why do I exist? Who are we as humans and why do we exist? When I was in college, I had a much more naïve view. I was very much into computers and artificial intelligence, and I thought it must be the case that I'm destined to work on some computer algorithms and, along with my colleagues, figure out how the brain works and how the computer can be as smart as the brain, perhaps even become a substitute of the brain, and that's what artificial intelligence is about. That was the simplistic view that I had. I pursued that in my college, in my graduate years. I went to Carnegie Mellon and got a PhD in speech recognition, then went to Apple, then SGI, then Microsoft, and then to Google. In each of the companies, I continued to work on artificial intelligence, thinking that that was the pursuit of how intelligence worked, and that our elucidation of artificial intelligence would then come back and tell us, "Ah, that's how the brain works." We replicated it, so that's what intelligence is about. That must be the most important thing in our lives: our IQ, our ability to think, analyze, predict, understand--all that stuff should be explicable by replicating it in the computer. I've had the good fortune to have met Marvin Minsky, Allen Newell, Herb Simon, and my mentor, Raj Reddy. All of these people had a profound influence on the way I thought. It's consistent that they too were pursuing the understanding of intelligence.

Last week, the White House announced plans to levy tariffs on up to $60 billion of Chinese imports. The primary, and legal, rationale hinges on the little-used Section 301 of a 1974 trade law that permits retaliation against countries that infringe US intellectual-property rights. Determined to halt what it perceives as a steady decline relative to an emergent China, the Trump administration and not a few voices in Congress are embracing a tough-on-China approach that they believe will at long last reassert American primacy. It will not; the strategy and the tactics of this trade war are a classic case of fighting not just the last war but fighting it on the adversary's terrain. Zachary Karabell is head of Global Strategies Envestnet and the president of River Twice Research.

We're now in a phase of computing increasingly characterized by engineering complex systems of automation by applying several new and convergent technologies including: deep learning, cloud computing and massive arrays of data-producing sensors. NVIDIA's deep learning GPUs have been at the center of partnerships or agreements with a multitude of companies and customers. For example, NVIDIA partnered with U.S.-based Tesla Motors to provide deep learning GPUs for autonomous driving, Japan-based FANUC Robotics to create a deep learning "factory manager" to oversee manufacturing robots that manufacture other manufacturing robots, U.S.-based Amazon Web Services to provide a web platform to create deep learning applications, China-based Hikvision to power the company's sophisticated systems of video surveillance, and Japan-based Komatsu's SMARTCONSTRUCTION mining and construction equipment vehicles. If you stop to take account of how many deep learning partnerships NVIDIA has entered into with powerful commercial entities in various sectors of global industry, it quickly becomes overwhelming. But how does NVIDIA and its manufacturing partners apply deep learning along the supply chain that produces NVIDIA GPUs?

The Chinese government has a massively ambitious plan to lead in the field of artificial intelligence by 2030. It's investing billions of dollars in a technology park in Beijing dedicated to AI. It wants to shape the standards that will govern the field. And it's fostering the development of impressive AI startups, which raised more money last year than American ones. At MIT Technology Review's annual EmTech Digital conference in San Francisco this week, several Chinese executives spoke about the advances their firms had made in AI.

In 2016, an Artificial Intelligence taught me how storytelling is moving from a nice-to-have to a must-have skill in the workplace. A few months ago, a TEDx talk I gave was analyzed by a deep learning system, an AI, developed at the University of Tokyo. The feedback and insights I got from the AI system were really interesting (it benchmarked and evaluated my talk against the database of all publicly-rated TED talks), but it also made me think about how tools like this AI could help make us all better public speakers and presenters. And it's not just speech feedback where AI is helping out. In an article I wrote for Fast Company, I described how startups are already selling services which use AI to create presentation slides for us, and they're getting better at it all the time.

Say you have a complicated task at hand, like reading the next paragraph of this article in a language you don't know. That's certainly daunting, but you can solve it easily with the help of an expert who does know the language, thanks to clever technology that exists today. Welcome to the world of artificial intelligence (AI), machine learning and cloud computing. If you think about it, these three elements exist all around us all the time. This is, after all, a website, and those are all on the Web, which is facilitated by the Internet. Today, cloud computing powers the Internet, while also needing the Internet to function.