Echoing Mr Topol's suggestion of greater stakeholder involvement in the development of medical applications, the role of low-code and no-code applications will come to the fore. In my previous blog, I spoke about low-code/no-code software, whereby staff drag-and-drop application components, connect them together and create a mobile or web app. These tools can empower staff in every department to be able to create their own internal applications to suit their needs, without writing any code or needing to bother the already stretched IT departments. These so-called "citizen developers", will have the means to create robust applications in a safe, scalable environment that has all of the tooling and procedures to ensure appropriate security, testing and sign-off as part of the NHS's Digital Transformation program.

Newswire) Investorideas.com, a global investor news source covering Artificial Intelligence issues a special edition of The AI Eye, looking at the battle for dominance between the US and China. On February 11, President Donald Trump issued an executive order on Maintaining American Leadership in Artificial Intelligence. The document stresses the importance of AI in propelling the US economy and cites current American global leadership in terms of R&D and deployment of AI as justifications for ramping up federal government commitments to promote the technology. Though it is not explicitly mentioned in the document, many commentators felt that the growing rivalry with China in the AI space influenced the President's executive order. Rob Verger, writing for Popular Science, captured the impression of those commentators when he observed: "Competition with China is a big part of the subtext to this announcement..." Some US AI companies were quick to respond.

BERLIN (Reuters) - The German Defense Ministry on Wednesday said it is evaluating separate bids from NATO and Canada to buy a high-altitude surveillance drone that has been parked at a German air base for years after the cancellation of the Euro Hawk program in 2013.

NASA is ready to put its drone traffic management system to the ultimate test and has chosen Nevada and Texas as its final testing sites. The agency, together with the FAA, has been developing an Unmanned aircraft Traffic Management (UTM) system over the past four years in an effort to figure out how to safely fly drones in an urban environment. Now that the project is in its last phase, it has teamed up with the Nevada Institute for Autonomous Systems in Las Vegas and the Lone Star UAS Center for Excellence & Innovation in Corpus Christi, Texas to conduct a final series of technical demonstrations. NASA and the FAA are planning to demo a big list of technologies, including their interface with vehicle-integrated detect-and-avoid capabilities, vehicle-to-vehicle communication and collision avoidance, as well as automated safe landing technologies. All those will help NASA understand the challenges of flying in an urban environment and conjure up ideas for future rules and policies.

I have worked on the problem of open-sourcing Machine Learning versus sensitivity for a long time, especially in disaster response contexts: when is it right/wrong to release data or a model publicly? This article is a list of frequently asked questions, the answers that are best practice today, and some examples of where I have encountered them. The criticism of OpenAI's decision included how it limits the research community's ability to replicate the results, and how the action in itself contributes to media fear of AI that is hyperbolic right now. It was this tweet that first caught my eye. Anima Anandkumar has a lot of experience bridging the gap between research and practical applications of Machine Learning.

University of Johannesburg and CIRANO; 4 / 46 AEA 2019 - Atlanta SKEMA Introduction Introduction China's rapid development have spurred large migration from rural areas to urban areas Between 1990 and the end of 2015 the proportion of China's population living in urban areas jumped from 26% to 56% Currently estimated by census, there are more than 240 million rural-to-urban migrants and more than 160 million working in cities outside of their hukou.

The Department for Health and Social Care (DHSC) has laid out 10 principles for the use AI and data driven tech in healthcare. They form the core of its new code of conduct for the technologies, aimed at ensuring their developers are focused on protecting patient data. Drawn up with the support of the industry, academics and patient groups, the code is aimed at making it easier for suppliers to develop technologies to treat conditions such as dementia, obesity and cancer, and to help health and care providers choose safe and effective solutions. Most of the 10 principles focus on issues already familiar to the debate around developing technology and data for public services. Define the outcome and how the technology will contribute to it. Use data that is in line with appropriate guidelines for the purpose for which it is being used.

Every year, it seems, pundits and egg-heads (like me) write down our predictions. Most of the time they are self-serving. However, looking into my crystal ball, I think 2019 is going to be a defining year at the intersection of physical and cybersecurity. The Internet of Things (IoT) and advances in artificial intelligence are some of the main driving forces in this evolution. Further, with chaos happening throughout the world, and the lead-up to a turbulent US presidential election, there has never been a more perilous--and opportunistic--time for those in the IoT and security business.

The race for Artificial Intelligence is launched. Like any technology, AI is not a risk in itself; it is its use that will determine the level and nature of the threats it is likely to cause. AI opens fabulous perspectives in the medical field, in the transport sector, even the protection of the environment. Nevertheless, these latest developments also draw a new spectrum of threats that we will attempt to outline, focusing on three specific types: military ethics, socio-political and geopolitical. In the military field, the use of AI is considered mainly from two angles, that of collaborative combat (between man and the "machine") and that of autonomous weapons.

President Donald Trump released a splashy new plan for American artificial intelligence last week. High on enthusiasm, low on details, its goal is to ramp up the rate of progress in AI research so the United States won't get outpaced by countries like China. Experts had been warning for months that under Trump, the US hasn't been doing enough to maintain its competitive edge. Now, it seems, Trump has finally got the memo. His executive order, signed February 11, promises to "drive technological breakthroughs ... in order to promote scientific discovery, economic competitiveness, and national security."