Smart Services Summit 2019 (hosted by Swiss Alliance for Data-Intensive Services) Location: Swisscom Business Campus, Turbinenstrasse 30, 8005 Zürich... We are happy to announce the 2nd Data Service Alliance Match-Making Event, to be held on October 2, 2019 from 1:00pm to 3:30pm, at FHNW camp... The General Assembly 2019 of the Data Service Alliance will take place on October 02, 2019 at FHNW campus, Riggenbachstrasse 16 (O... In collaboration with Zazuko Knowledge Graphs are getting a lot of attention in the industry and the public sector. CLEF 2019 is the 10th CLEF conference continuing the popular CLEF campaigns which have run since 2000 contributing to the systematic evaluation of inf... Organised by: University of Zurich, Digital Society InitiativeOn Monday September 16, the Digital Society Initiative of University of Zurich is organi... AI, big data and XR are transforming the industry from its core again & in order to utilize the full potential, international collaboration and ma...

Armed forces in Latin America & the Caribbean are faced with the challenge of having to operate with a multi-dimensional mandate. In times of heightened civil unrest they are required to undertake peace-keeping operations, gang warfare driven by the arms-for-drugs trade calls for counter-insurgence style deployments and seasonal natural disasters often require their services to support the essential services under extreme conditions. With limited resources, every opportunity to prevent the unnecessary expenditure while maintaining effectiveness needs to be taken. In this post I will demonstrate how the application of the K-means clustering algorithm, in the context of how Naval Forces in Latin America and the Caribbean, can be used to schedule efficient Naval deployments and reduce the number of unnecessary operations. For this example I simulated 200 data points that represent the location of incidents that would result in the need for Naval resources to be deployed in the Caribbean Sea. The data have a timestamp that indicates the time of day of each incident on a 24-hour clock cycle.

Ethics in machine learning are what comes to mind when we imagine a worst case scenario in the context of artificial intelligence. As an example, we can think of HAL 9000 from '2001: A Space Odyssey' and Skynet from the'Terminator' films or more recently Ultron from the'Avengers'. Sadly, the main thinking behind most of the depicted self aware artificial intelligences is that they become sentient with the sole purpose of destroying the human race to ensure its survival. While such a scenario is not impossible or thankfully a ways off from this type of dystopian future. There are however pressing ethical matters in AI that we need to be considering right now.

The Ministry of Defence has identified a range of emerging technologies it intends to explore as part of a "transformed approach to using and procuring technology". The MoD has this week published the Defence Technology Framework, a 56-page document which lays out a vision for the role the science and tech sectors could play in the work of the ministry and the Armed Forces. The framework identified seven "technology families" it sees as being of most significance. The first of these is "advanced materials", which includes areas such as nanotechnology, 3D printing, and synthetic biology. The second area picked out by the MoD is artificial intelligence, machine learning, and data science, while the third is autonomous systems and robotics.

Around the world governments are looking for mechanisms that explain to users how algorithms are making decisions - how and why they get shown what content or ads they see, text or voice assistant protocols, and more. The European Commission started the 2nd phase of the Algorithmic Awareness Raising pilot project. The project originally came at the request of the European Parliament, publishing a call for tender for an Exploratory Study on Governance and Accountability Mechanisms for Algorithmic Systems. The Algorithmic Awareness Raising pilot project (a 16 month study that began in March 2018) has analysed the state-of-the-art in algorithmic decision-making, including academic literature and an index of policy, regulatory, civil society and industry approaches, and is exploring case studies for specific areas of application. Building on the first study, the second phase of the project will focus more in detail on two emerging policy tools for addressing risks and furthering the understanding of algorithmic decision-making systems.

The U.S. National Institute of Standards and Technology (NIST) is developing a plan for federal engagement in the development of AI technical standards and related tools. This is in response to President Trump's Executive Order on Maintaining American Leadership in Artificial Intelligence. Click here to watch the video.

The fifth generation of mobile telecommunications standards, 5G, is not the linear extension of the four previous generations (1G, 2G, 3G and 4G) that have emerged over the last thirty years. On the contrary, the set of technologies underpinning this latest standard will make 5G the disruptive generation, the generation that will utterly transform the economy. There are three main reasons for this. First, 5G will boost capacity enormously, and not just in terms of theoretical performance, as early demonstrations have shown. Second, 5G will be disruptive because of its extremely low latency.

Source: Capital IQ; Pitchbook; Deallogic; S&P; McKinsey Global Institute "Overall Europe is behind in private investments in Artificial Intelligence" AI strategy for Europe* * COM(2018)/237 Total VC Investments in Blockchain (2010-2018) • North America: $5,1 billion (Canada: $623 Mill.) • China: $1.5 billion • Europe: $1,2 billion (CH:$414 Mill.&

The general premise of this article is different from most of my previous AI Power articles. While most of the articles in this series have related to the near-term struggles for power between organizations and governments with regards to regulation, data, and international policy, this article will focus on the long-term trajectory that AI and technology are headed towards and what that means for the most powerful nations and organizations. In the long term (15-40 years ahead), the power struggles around AI will not end with economic and military competition. Ultimately, AI power will involve determining the trajectory of intelligence itself. This might involve the creation of astronomically powerful artificial general intelligence (AGI) and/or the creation of vastly more capable and powerful cognitively enhanced humans (transhuman transition).

Artificial intelligence (AI) is of great strategic importance to the United States. We are recognized as the current leader in the space, and as such, are investing in capabilities and opportunities to ensure we are progressing AI forward across the country. AI is instrumental in providing the country with a competitive advantage. If we're not raising the bar in the United States, other countries will become more adept leaders in the space. AI is a top priority at the federal level right now.