It's time for AI startups to step up and use their formidable technology expertise in AI to help get ... [ ] more Americans back to work now. Bottom Line: A.I.'s ability to predict and recommend job matches will help get more Americans back to work, helping to reduce the 16.8 million unemployed today. One in ten Americans is out of work today based latest U.S. Department of Labor data. They're primarily from the travel and hospitality, food services, and retail trade and manufacturing industries, with many other affected sectors. McKinsey & Company's recent article, A new AI-powered network, is helping workers displaced by the coronavirus crisis provides context around the scope of challenges involved in closing the unemployment gap.

Better internet access, high transmission rates, low delay and broad bandwidth would deliver military advances, such as gathering intelligence, visualising combat operations and delivering precise logistical support. The article added: "Based on the 6G network, the commander could make the right decisions quickly after the control-and-command network mined, learned and analysed vast data from the ground," The China National Defence News report said that battle units could get highly specific and instantaneous information on troop locations and equipment, allowing the military to make tailored logistic plans. China officially started researching the 6G telecoms technology in early November, according to a Ministry of Science and Technology notice. The ministry announced that it had two teams overseeing 6G research.

NEW YORK - The Pentagon is adopting new ethical principles as it prepares to accelerate its use of artificial intelligence technology on the battlefield. The new principles call for people to "exercise appropriate levels of judgment and care" when deploying and using AI systems, such as those that scan aerial imagery to look for targets. Defense Department officials outlined the new approach Monday. "The United States, together with our allies and partners, must accelerate the adoption of AI and lead in its national security applications to maintain our strategic position, prevail on future battlefields, and safeguard the rules-based international order," said Defense Secretary Mark Esper. It follows recommendations made last year by the Defense Innovation Board, a group led by former Google CEO Eric Schmidt.

The SETI Institute, a Silicon Valley-based nonprofit that seeks to explore and explain the nature and origins of life in the universe, is gearing up to host the fifth iteration of its competitive, NASA-funded summer program, the Frontier Development Lab. FDL brings together a diverse cadre of researchers each year since its inception to rapidly leverage artificial intelligence, machine learning and advanced computing capabilities--all to ultimately help America's space agency accelerate its own research and discoveries. While SETI envelops the "search for extraterrestrial intelligence," its inside efforts touch a range of areas across space, science and beyond. But the 2020 program might run a little differently than those that came before. "Now, what's interesting is, we may--for the first time actually--undertake the program virtually because of the COVID-19 pandemic," Bill Diamond, president and CEO of the SETI Institute, told Nextgov recently. "All indications are that this is going to be with us through at least the early part of the summer, and it may preclude the in-person working system that normally is characterized by the FDL program."

We may not be living on Mars or traveling to work using jet packs, but there's no doubt the coming decade will bring many exciting technological advances. In this article, I want to outline the 25 key technology trends that I believe will shape the 2020s. The increasing ability of machines to learn and act intelligently will absolutely transform our world. It is also the driving force behind many of the other trends on this list. This refers to the ever-growing number of "smart" devices and objects that are connected to the internet.

A team of Army and industry researchers have developed a metric for neural networks--computing systems modeled loosely after the human brain--that could assess the reliability and confidence of the next generation of artificial intelligence and machine learning algorithms. Deep neural network, or DNNs, are a form of machine learning that use training data to learn. Once trained, they can make predictions when given new information or inputs; however, they can be easily deceived if the new information is too far outside its training. Researchers said given the diversity of information in training data and potential new inputs, coming up with a solution is challenging. "This opens a new research opportunity to create the next generation of algorithms that are robust and resilient," said Dr. Brian Jalaian, a scientist at the U.S. Army Combat Capabilities Development Command's Army Research Laboratory.

The algorithmic revolution is here, and nations are losing control of not only their understanding of the potential impact of artificial intelligence but also the governance model that enforced accountability on the advances in science and technology over the years at all levels. While each new technology innovation claims its territory for the economic advances in the human ecosystem with significant ramifications across cyberspace, geospace and/or space (CGS), the rise of artificial intelligence (AI) has not only undermined governance, management, and growth models, but it has also broken all barriers to boundaries defined by human decision makers. In addition, it is both blurring the boundaries between human intelligence and machine intelligence, and the boundaries between man and machine and real and fake. As a result, the power dynamics are shifting away from the select few across nations (and is moving away from humans entirely to algorithms)--re-defining the criteria upon which geopolitics was framed--and thereby threatening the foundations of global peace and security. Since the beginning of the technological age, each new idea, innovation, and invention has helped humans across nations usher in a new era of economic growth, changing the fundamentals of respective nations and their security.

As the COVID-19 pandemic rages on unabated in countries around the world, there's a shared desire among those forced to shelter in place to see the extent to which social distancing is slowing the disease's spread. It's understandable -- collateral damage from government-imposed business closures threatens to devastate entire industries. As of this week, 26 million Americans have filed for unemployment claims, according to the U.S. Bureau of Labor Statistics, and the International Monetary Fund predicts a global financial crisis rivaling the Great Depression. Fortunately, a preprint study published by researchers at the University of Texas, the Southwest Research Institute, and the University of Texas Health Science Center in San Antonio strongly implies that quarantining and physical distancing are having the intended effects. Using a hybrid AI system dubbed SIRNet and several epidemiological models, which were trained on smartphone location data along with population-weighted density and other data points from the startup Safe Graph, World Health Organization, the U.S. Centers for Disease Control and Prevention, and elsewhere, the coauthors claim they managed to accurately predict the outcomes of various social distancing policies.

In the past few years, AI has advanced our technology at an incredible rate. From completely automating labor-intensive jobs to diagnosing lung cancer, AI has achieved feats previously thought impossible. However, in the wrong hands, an algorithm can be a destructive weapon. To ensure that malicious actors don't wreak havoc in our society, there are several key challenges which we have to solve. The real danger of AI is not the rise of a sentient algorithm like SkyNet taking over the world.

In early 2009, the Google Self-Driving Car Project was born, evolving over the years into what we now know as Waymo. Not long after the project started, Google founders Sergey Brin and Larry Page challenged engineers to drive autonomously without human intervention or disengagements along ten challenging 100-mile routes in Google's home state of California. Yes, that was long before state governments started granting licenses for driverless car testing on public roads. The first state to issue such a license was Nevada in May 2012, with California doing the same only in September 2014. So how did Google get away with testing fully-autonomous cars on public roads in California in 2009?