If you hadn't heard, Elon Musk is worried about the machines. Though that may seem a quixotic stance for the head of multiple tech companies to take, it seems that his proximity to the bleeding edge of technological development has given him the heebie-jeebies when it comes to artificial intelligence. He's shared his fears of AI running amok before, likening it to "summoning the demon," and Musk doubled down on his stance at a meeting of the National Governors Association this weekend, telling state leaders that AI poses an existential threat to humanity. "Until people see robots going down the street killing people, they don't know how to react because it seems so ethereal. AI is a rare case where I think we need to be proactive in regulation instead of reactive. Because I think by the time we are reactive in AI regulation, it's too late," according to the MIT Tech Review.

A drone flies May 11, 2017, in the showroom of the DJI headquarters in Shenzhen, China. A Chinese company that is the world's largest drone manufacturer said Friday it is "surprised and disappointed" by reports the U.S. Army has halted use of its remote-controlled aircraft because of cyber vulnerabilities. An Army memo Wednesday, obtained by sUASnews.com The memo from Lt. Gen. Joseph Anderson, the deputy chief of staff, cited possible threats from any DJI electrical components, software, cameras, radios, GPS units or handheld controllers, the publications reported. It ordered U.S. Army personnel to uninstall all DJI applications and remove all batteries and media storage devices.

This is a very, very problematic prosecution to my mind, and I think it's bizarre that the United States government has chosen to prosecute somebody who's arguably their hero in the WannaCry malware attack and potentially saved lives and thousands, hundreds of thousands, if not millions, of dollars over the sale of alleged malware,

At Black Hat last week, you couldn't pass a slot machine without some cybersecurity technology vendor crowing about machine learning or artificial intelligence (AI). Yup, machine learning algorithms have great potential to help with security analytics and employee productivity, but this technology is in its infancy and not well understood. ESG asked 412 cybersecurity professionals to assess and characterize their knowledge of machine learning/AI as it relates to cybersecurity analytics and operations technologies. Of the total survey population, only 30% of respondents claim to be very knowledgeable in this area. In other words, 70% of cybersecurity professionals really don't understand where machine learning and AI fit. Furthermore, cybersecurity pros were asked if their organizations have deployed or plan to deploy machine learning/AI technologies for cybersecurity analytics and operations.

Alphabet-owned Artificial Intelligence laboratory DeepMind is bankrolling NHS research, Business Insider has revealed. The London-based company has provided Moorfields Eye Hospital's trust with £110,000 in funding since July 2016-- when the two organisations kick-started a partnership to test DeepMind's new technology to diagnose eye diseases. The collaboration had already sparked controversy, as over one million patient data were processed by DeepMind's algorithm: this raised questions on patients' consent to data treatment and the opportunity of sharing clinical data with a private technology corporation. Business Insider, which obtained the information under an FOI request, says that DeepMind's payment went to cover "the costs incurred by the [Moorfields Eye Hospital's] Trust", rather than being a fee to access patient data. The hospital did not pay any money to DeepMind.

But just such a change appears to be happening now. In a great wave of technological change, sensors are spreading through factories and warehouses, software is predicting the need for maintenance before a machine breaks down, power grids and loading docks are becoming intelligent, and custom-designed parts are being produced on demand. The leaders of the next industrial revolution are companies making advances in fields such as robotics, machine learning, digital fabrication (including 3D printing), the Industrial Internet, the Internet of Things (IoT), data analytics and blockchain (a system of decentralized, automated transaction verification). Because these technologies all reinforce the others' impact, they are leading to a new level of proficiency, and to new types of opportunities and challenges for business and for society at large. One key indicator is that conventional boundaries between industries are eroding. It's getting harder to tell the difference between, say, a telecommunications company and an entertainment producer, or between a retail bank and a retail store. The relationships among suppliers, producers, and consumers are also blurring, more rapidly than many business decision makers are prepared for. The foundation of business strategy has long been the classic value chain, which links together raw materials producers, manufacturers, distributors, and (in the end) consumers through a well-established commercial infrastructure characterized by a stable set of transactions. But the rise of digital technology enables individuals to connect outside the value chain and deliver more efficient, effective products and services. This will reduce the importance of economies of scale and conventional divisions of labor. Relationships among companies will be more fluid and the price and cost of goods and services more volatile than they are today.

While EMMA is a relatively simple application, developers are thinking bigger as well: Today's cognitive technologies can track the course, speed, and destination of nearly 2,000 airliners at a time, allowing them to fly safely.4 Over time, AI will spawn massive changes in the public sector, transforming how government employees get work done. It's likely to eliminate some jobs, lead to the redesign of countless others, and create entirely new professions.5 In the near term, our analysis suggests, large government job losses are unlikely. But cognitive technologies will change the nature of many jobs--both what gets done and how workers go about doing it--freeing up to one quarter of many workers' time to focus on other activities.

In this sponsored post, Ramnath Sai Sagar, Marketing Manager at Mellanox Technologies, explores how recent advancements in Artificial Intelligence, especially deep learning, are set to make an impact in the field of astronomy and astrophysics. Since the dawn of the space age, unmanned spacecraft have flown blind, with little to no ability to make autonomous decisions based on their environment. That, however, changed in the early 2000s, when NASA started working on leveraging Artificial Intelligence (AI) and laying the foundation that would help Astronauts and Astronomers to work more efficiency in Space. In fact, just last month, NASA's Jet Propulsion Laboratory published how AI will govern the behavior of space probes. Recent advancements in Artificial Intelligence, especially Deep Learning (a subfield in AI), are set to make a deeper impact in the field of astronomy and astrophysics.

One of the branches of the United Nations is the International Labor Organization (ILO), which, among other duties, compiles data from the global job market. These data show the dominance of the service sector over the agricultural and manufacturing sectors with respect to the number of people employed. Globally, it is estimated that by the end of 2017 about 46% of the job market will be engaged in service sector activities -- but if only developed economies are considered, the number rises to a staggering 74%. We are talking about three out of four workers. In light of technological advances, the agricultural sector -- a major source of income for underdeveloped countries -- employs an ever smaller share of the population.

Over the past year firms like AggregateIQ and Cambridge Analytica have been credited with using AI-targeted ads on social media to help swing the Brexit referendum and the US presidential election respectively. But a lack of evidence meant we have never known whether the technology exists to make this possible. Now the first study detailing the process from start to finish is finally shedding some light. "This is the first time that I've seen all the dots connected," says Joanna Bryson, an artificial intelligence researcher at the University of Bath, UK. At the heart of the debate is psychographic targeting – the directing of political campaigns at people via social media based on their personality and political interests, with the aid of vast amount of data filtered by artificial intelligence.