It all started at Baledogle, the old Soviet airport 70 miles northwest of Mogadishu, Somalia's capital, where the U.S. runs a deeply clandestine drone operation with around 30 to 40 American personnel. While shrouded in secrecy, Baledogle has reportedly grown over the years into a key point for training Somali commandos and, early last month, for launching a joint strike against al-Shabab. The radical Islamist group grew out of the splintered factions of Sharia-based courts that filled the vacuum of authority after a U.S.-led coalition withdrew from the country in the early 90s. Today, al-Shabab sees itself as the preeminent terror force in Somalia with global ambitions. "These folks are honing their skills in a local conflict that is part of a global war they are waging against the United States," said Katherine Zimmerman, an expert on Al Qaeda at the American Enterprise Institute. Al-Shabab regularly attacks foreigners, including aid workers and Somalis, as it wages an insurgent fight against the U.S.-leaning government.

The convergence of artificial intelligence (AI) -- machine learning -- increased global mobile connectivity, the Internet of Things, heightened computing power, virtual and augmented reality, and nanotechnology will produce a data tsunami that will require most organizations to transform how they do business. The magnitude of the coming disruption is mindboggling. One major aspect of this disruption will be the impact on employment and the resulting loss of global consumer purchasing power. According to research from the Martin School at Oxford University and Citi published in January 2016, technology has a high probability of automating 57 percent of the jobs in the Organization for Economic Cooperation and Development countries, as compared to 47 percent of the jobs in the United States alone. The corresponding high risk of job automation numbers for China is 77 percent, India is 69 percent, South Africa is 67 percent and Ethiopia is 85 percent.

Advancements in Artificial Intelligence -- the capability of machines to make informed decisions and perform tasks usually reserved for humans -- are moving at a rapid rate, and it's threatening workers from truck drivers to surgeons, according to a new study from the University of Oxford. Spearheaded by Katja Grace of the Future of Humanity Institute at Oxford, the report surveyed more than 350 AI experts on how long it'll take machines to master certain jobs, from remedial to advanced. Within the next decade, experts predict machines will outperform humans when it comes to translating languages, writing a quality high school essay, and driving trucks. AI proficiency in sales and retail is expected by the early 2030s. The essay data is especially intriguing.

In an article published on the CAF website, Rhodri Davies, programme leader at Giving Thought, an in-house think tank at CAF, says that artificial intelligence could help make philanthropy advice a "mass-market commodity" widely available to the public, rather than the preserve of the rich. The article also says artificial intelligence could reduce the cost to charities of giving advice to potential donors, help people choose how to donate and decide what they want to achieve with their donation, and help maximise social outcomes and donor satisfaction. Artificial intelligence could even become a new charitable cause as it becomes more commonplace, a second article by Davies suggests. There are a number of examples of the use of artificial intelligence by charities, including the use of chatbots and personal assistants, it says. For example, it mentions a project in which Arthritis Research UK partnered with Microsoft to pilot a chatbot that can give users tailored advice on arthritis, which Davies says shows how artificial intelligence can help the charity sector.

Tools OneSpin revealed new formal applications focused on random fault verification for safety critical analysis in automotive and other mission-critical applications. The Fault Injection App provides controlled injection of faults and assertion mapping to associated fault scenarios, as well as visibility into corrupted design behavior. The Fault Detection App allows the detection of dangerous random faults or faults not detected by the safety mechanism. Additionally, the Fault Propagation App was updated to include a new debugger and support for SystemVerilog Assertions (SVA) and Property Specification Language (PSL). Cadence launched VirtualBridge Adapter, a virtual emulation technology allowing user applications and OS drivers to establish a virtual protocol connection to Palladium platforms.

In the tech space, these terms have been used a lot and sometimes interchangeably without understanding what they mean. So what is all the fuss about? Before we get to why you should care, let us first clear up the confusion of what each is all about and how it came to be. AI is simply human intelligence expressed by a machine. Well of course not, human intelligence on its own is a complex thing and replicating it is no easy task.

In October 2016, a worldwide denial-of-service (DDoS) attack crippled the internet, infecting thousands of devices with malware that spread through home cameras, DVRs, and other connected devices. The malware doing the damage was not extremely sophisticated -- but neither were the malware protections or user IDs and passwords that were easily detected and spoofed to break into home devices. In a nutshell, the Internet of Things (IoT), which consists of sensors, cameras, DVRs, mobile phones, and so on, that communicate over public internet, is extremely vulnerable. Meanwhile, corporate auditors are only now beginning to get their arms around how they vet companies for IoT security protection. "Modern businesses are digital hives of connected objects that all too often lack adequate security, providing attractive gateways for cyber attackers," said IoT security expert Dave Palmer, director of technology for Darktrace. That could be anything from a printer or a thermostat connected to the corporate network, through to a connected coffee machine or iWatch."

Brain has intrigued researchers since the beginning of scientific endeavors. Firstly, beginning of computers saw the advent of exciting developments which culminated to the development of the new discipline of artificial neural networks (ANN). ANNs have been through several generations of major developments, with the recent phase consisting of spiking neural networks based works [1]. Another parallel field of computational neuroscience has been the bio-inspired cognitive architectures (BICA) [2] a field which got major thrust in development. Cognitive architecture (CA) in general and BICA in particular also has a long history and the efforts have been devoted towards trying to emulate the functioning of brain. CAs like SOAR and ACT-R have been under development for many decades and have been applied in various studies [3, 4].

Here are 110 upcoming meetings and conferences, for June 2017 and beyond. You can also find the latest list on KDnuggets Meetings page Color code: Business-Oriented meetings in Blue, Research meetings (with calls for papers and program committee) in green Top countries: India, France, Australia: 3 For the second month in a row, London is the top city: Washington DC, New Orleans, Houston, Chicago, Atlanta: 3 June 2017 Jun 1-2, Deep Learning in Finance Summit. Mention "KDNuggets" and save 18% on tickets. Use code KDNUGGETS to save 15%. Use code KDNUGGETS_DSC17 to save.

Race does not stand up scientifically, period. To begin with, if race categories were meant primarily to capture differences in genetics, they are doing an abysmal job. The genetic distance between some groups within Africa is as great as the genetic distance between many "racially divergent" groups in the rest of the world. The genetic distance between East Asians and Europeans is shorter than the divergence between Hazda in north-central Tanzania to the Fulani shepherds of West Africa (who live in present-day Mali, Niger, Burkina Faso, and Guinea). Armed with this knowledge, many investigators in the biological sciences have replaced the term "race" with the term "continental ancestry." This in part reflects a rejection of "race" as a biological classification. Every so-called race has the same protein-coding genes, and there is no clear genetic dividing line that subdivides the human species.