The South Western Command will be holding a two-day brain-storming session with top military officers, scientists and IT experts on "AI in mechanised (tanks and infantry combat vehicles) warfare" at Hissar next week Rajnath Singh is likely to announce "25 defence-specific AI products" that will be developed by 2024 The South Western Command will be holding a two-day brain-storming session with top military officers, scientists and IT experts on "AI in mechanised (tanks and infantry combat vehicles) warfare" at Hissar next week Rajnath Singh is likely to announce "25 defence-specific AI products" that will be developed by 2024 NEW DELHI: The Army now wants to harness the potential of artificial intelligence (AI) to bolster its combat lethality and survivability, even as the 13-lakh force is testing its new integrated battle groups (IBGs) geared towards mobilising fast and striking hard across the borders. With China taking huge strides in the ongoing global race to develop AI-powered weapon and surveillance systems for futuristic wars, with a special focus on developing lethal autonomous weapon systems (LAWS), India obviously does not want to miss the bus. "China is employing AI (basically simulation of human intelligence processes by computers) in the defence arena in a big way. But we can catch up because we have the required IT (information technology) brains in India. Our aim is to examine how AI can help us become more lethal and effective in our war-fighting in a flexible and dynamic battlefield," said South Western Command (SWC) chief Lt-General Alok Kler, speaking to TOI on Friday.

Two new and seemingly unrelated approaches to delivering healthcare are starting to take shape in the industry: the use of artificial intelligence, and the integration of social determinants of health in crafting care plans. Both trends are developing independently, but they're likely due to intersect; factoring in SDOH is possible due to data, and if AI shines in any one particular area, it's making sense of complex data sets. If the social determinants are comprised of the socioeconomic factors that can influence a person's health -- income, education, access to transportation, etc. -- then AI has the potential to allow providers to make the best possible use of that information. That becomes increasingly important as value-based care emerges. With reimbursement increasingly tied to health outcomes, providers have a real incentive to ensure they're delivering the best care possible.

Economics has experienced an empirical turn in the last few decades. We have entered an era of big data, machine learning, and artificial intelligence. Experimental methods have greatly increased in importance in both the social and life sciences. And recent efforts at reforming the publication system promise to improve the replicability and credibility of published findings. One might be tempted to conclude that this increased availability of and reliance on quantitative evidence allows us to dispense with the normative judgements of earlier days. I will argue that the opposite is the case. The choice of objective functions, which define our goals, and of the set of policies to be considered matters ever more in all of these contexts. A famous example in debates about the dangers of artificial intelligence (AI) is the hypothetical AI system with the objective of producing as many paperclips as possible. If sufficiently capable, such an AI system might end up annihilating humanity in the pursuit of this objective. Another example is the design of experiments. The majority of experiments in the social and life sciences are designed based on the (implicit) objective of obtaining precise estimates of causal effects. Such experiments randomly assign treatments using fixed probabilities.

Overview The goal of artificial intelligence is to enable the development of computers to do things normally done by people -- in particular, things associated with people acting intelligently. In the case of cybersecurity, its most practical application has been automating human intensive tasks to keep pace with attackers! Progressive organizations have begun using artificial intelligence in cybersecurity applications to defend against attackers. However, on it's own, artificial intelligence is best designed to identify "what is wrong." What today's enterprise needs to know is not only "what is wrong" in the face of a breach, but to understand "why it's wrong" and "how to fix it!"

Maria Bartiromo explores the bounds of artificial intelligence usage globally. From health care to the transportation industry, FOX Business' Maria Bartiromo looks at how artificial intelligence (AI) is shaping the future of society. In February the U.S. government launched an American AI initiative, which aims to stimulate AI development. The government's investments in unclassified R&D for AI technologies is up 40 percent since 2015 and for the first time in history, President Trump's fiscal year 2019 budget requests to designate AI and unmanned autonomous systems a priority. However, some say the problem is that China spends much more on AI investment and financing. In 2017, AI spending hit $39.5 billion, with China accounting for 70 percent of the expenditures.

Artificial intelligence is infiltrating every industry, allowing vehicles to navigate without drivers, assisting doctors with medical diagnoses, and mimicking the way humans speak. But for all the authentic and exciting ways it's transforming the tasks computers can perform, there's a lot of hype, too. As Jeremy Achin, CEO of newly minted unicorn DataRobot, puts it: "Everyone knows you have to have machine learning in your story or you're not sexy." The inherently broad term gets bandied about so often that it can start to feel meaningless and gets trotted out by companies to gussy up even simple data analysis. To help cut through the noise, Forbes and data partner Meritech Capital put together a list of private, U.S.-based companies that are wielding some subset of artificial intelligence in a meaningful way and demonstrating real business potential from doing so. One makes robots that can whir around shoppers to help workers restock shelves. Another scans recruiting pitches for unconscious bias. A third analyzes massive data sets to make street-by-street weather predictions. To be included on the list, companies needed to show that techniques like machine learning (where systems learn from data to improve on tasks), natural language processing (which enables programs to "understand" written or spoken language), or computer vision (which relates to how machines "see") are a core part of their business model and future success. Find all the details on our methodology here. The honorees span categories like human resources, security, insurance, and finance, with healthcare, transportation, and infrastructure startups best represented on the list.

Historically, the MixMode platform has provided its users with a forensic hunting platform with intel-based Indicators and Security Events from public & proprietary sources. While these detections still have their place in the security ecosystem, the increase in state-sponsored attacks, insider threats and adversarial artificial intelligence means there are simply too many threats to your network to rely on solely intelligence-based detections or proactive hunting. Many of these threats are sophisticated enough to evade traditional threat detection or, in the case of zero-day threats, signature-based detection may not even be possible. In the face of this growing threat, the best defense is to supplement these traditional methods with anomaly detection, a term that is quickly becoming genericized as it is rapidly bandied about within the industry. Here we will discuss some of the opportunities and challenges that can arise with anomaly detection as well as MixMode's unique approach to the solution.

Making a political donation to a presidential campaign is about to get as easy as -- well, saying it out loud. Starting next month, users of voice-controlled home assistant Amazon Alexa will be able to dictate their donations to a 2020 presidential campaign: "Alexa, I want to make a political contribution," or "Alexa, donate [amount] to [candidate name]." Alexa users can make donations of at least $5 and up to $200 to campaigns, and the feature is currently limited to presidential campaigns. Campaigns can sign up starting Thursday. The latest evolution in campaign technology raises new questions about how such contributions will be screened to make sure they are legal.

From health care to the transportation industry, FOX Business' Maria Bartiromo looks at how artificial intelligence (AI) is shaping the future of society. In February the U.S. government launched an American AI initiative, which aims to stimulate AI development. The government's investments in unclassified R&D for AI technologies is up 40 percent since 2015 and for the first time in history, President Trump's fiscal year 2019 budget requests to designate AI and unmanned autonomous systems a priority. However, some say the problem is that China spends much more on AI investment and financing. In 2017, AI spending hit $39.5 billion, with China accounting for 70 percent of the expenditures. "AI is growing by leaps and bounds.

Mr. Yiannouka is the CEO of the World Innovation Summit for Education (WISE), a global think tank of the Qatar Foundation. WISE is dedicated to enabling the future of education through innovation. Its activities encompass research, capacity-building programs, and advocacy. WISE flagship initiatives include an annual series of research publications, a biennial global summit dubbbed the'Davos of education', the WISE edTech Accelerator, the WISE Innovation Awards, and the WISE Words podcast. Prior to joining WISE in August 2012, Stavros was the Executive Vice-Dean of the Lee Kuan Yew School of Public Policy (LKY School) at the National University of Singapore.