The high-powered knowledge event was held at Atlantis The Palm on 19 November 2017, and brought together the UAE's smartest data professionals to explore new applications for machine learning and artificial intelligence. The speaker roster included decision-makers from Cloudera, AXA Gulf, DU Telecom, Etihad Airways, Microsoft and Wipro. Machine learning is helping companies detect fraud, predict their customers' behaviour, analyse consumer preferences to suggest products, and offer proactive customer support. Combined with big data, machine learning algorithms are sifting through terabytes of data to predict market movements and help derive competitive advantage. "We are very pleased to be able to bring such a high-quality cohort of data professionals and people on the cutting edge of technology to the same platform with the Cloudera Sessions Dubai 2017.
Airbus is looking to develop autonomous aircraft and technologies that will allow a single pilot to operate commercial jetliners, helping cut costs for carriers, chief technology officer Paul Eremenko said. "The more disruptive approach is to say maybe we can reduce the crew needs for our future aircraft," Mr Eremenko told Bloomberg Television's Yvonne Man in an interview broadcast on Wednesday. "We're pursuing single-pilot operation as a potential option and a lot of the technologies needed to make that happen has also put us on the path towards unpiloted operation." The aerospace industry has begun seeing a similar trend as the car market, where carmakers are investing in or acquiring autonomous driving startups. Plane manufacturers including Airbus and Boeing are racing to develop artificial intelligence that will one day enable computers to fly planes without human beings at the controls.
Companies that are able to adapt to a world where innovation is increasingly driven by machine learning, or artificial intelligence more broadly, are the ones that will come out the other end of the tunnel and thrive, according to Oliver Rees, GM of Torque Data at Virgin Australia. Rees, whose data analytics consultancy firm Torque Data was acquired by Virgin Australia in 2015, told ZDNet that one of its tasks has been "reengineering [Virgin's] analytical capability", ensuring the airline is well-prepared to embrace the opportunities that are offered by machine learning. While not new to machine learning, Virgin Australia has been seeking better methods of developing, applying, and assessing machine learning algorithms, recently turning to Massachusetts-based company DataRobot, which operates on the belief that automated machine learning will not only increase productivity for data scientists, but also open up the world of data science. Rees told ZDNet that Torque, as the data analytics arm of Virgin, has been investigating ways to improve customer experience for members of Virgin's Velocity Frequent Flyer loyalty program. "We want people within our program to be able to redeem points for great experiences, and to do that, we want to be able to better predict when is the best time for particular people to redeem points and what should they be redeeming them against," Rees said.
DJI is inviting state, local and tribal governments to consider partnering with the company as they apply to take part in the Federal Aviation Administration's (FAA) new UAS Integration Pilot Program. According to DJI, the program smartly provides opportunities for government and industry to experiment with advanced drone operations and test new forms of airspace management. The company notes it is pleased that the program will also help inform policymakers on regulatory approaches to safe drone adoption. "DJI has worked for years with government officials around the world to help develop reasonable, safety-enhancing public policies while keeping open the pathways to innovation," says Brendan Schulman, DJI's vice president of policy and legal affairs. "We would very much value the opportunity to work with U.S. state, local and tribal governments to develop smart and comprehensive strategies for expanding how drones can benefit their constituents while properly managing their integration into the airspace."
I'm a sucker for bio-inspired engineered. This air-and-sea drone, called the Aquatic Micro Air Vehicle, or AquaMAV, had my number from the first splash. The drone can fly up to 25mph and cover a distance of more than six miles on a charge. After it dives, it can collect water samples and then relaunch itself out of the water using a powerful gas jet. Developed by Mirko Kovac, PhD, who directs the Aerial Robotics Lab at Imperial College London, the device is one of a growing number of multi-domain robots that can traverse disparate environments.
An unidentified aircraft was seen flying among other airliners in skies above Oregon - causing confusion among air traffic control and the Air Force, which sent F-15s to investigate. The aircraft flew over Oregon on October 25, with no flight plan, no active identification transponder or transmitting collision avoidance signals. While information about plane's pilot or intended destination remain unclear, some have suggested that the aircraft was trafficking drugs. Additionally, it is believed that the mysterious flight could be a potential breach of national security. An unidentified aircraft flew over Oregon on October 25, with no flight plan, no active identification transponder or transmitting collision avoidance signals.
There is a growing crisis in the world of analytics and cognitive technologies, and as of yet there is no obvious solution. The crisis was created by a spate of good news in the field of cognitive technology algorithms: they're working! Specifically, a relatively new and complex type of algorithms--deep learning neural networks (DLNN)--have been able to learn from lots of labeled data and accomplish a variety of tasks. They can master difficult games (Go, for example), recognize images, translate speech, and perform many more tasks as well as or better than the best humans. So other than the threat to our delicate human egos and jobs, what's the problem?
A state-of-the-art drone flying simulator called DRL Simulator is out on Steam today and it's as close to the real thing as you're going to get without spending hundreds of dollars on a high-end drone. DRL Simulator was created by the Drone Racing League (DRL), the premiere competitive league for professional drone racing. The simulator goes through all the basics of drone piloting, allowing people to get a feel for what it's like to fly a real drone, and works all the way up to the most difficult professional levels of drone racing. The simulator is so true-to-life that DRL is actually using it to host tryouts to its 2018 competitive drone racing season, with the top simulator pilots getting a chance to earn thousands of dollars. Drone racing is actually one of the few things that you can practice virtually and have it translate pretty much 1:1 to real-world application.
A year ago, the AI Now Institute released its inaugural report on the near-future social and economic consequences of AI, drawing on input from a diverse expert panel representing a spectrum of disciplines; now they've released a followup, with ten clear recommendations for AI implementations in the public and private sector. The first of these is "Core public agencies, such as those responsible for criminal justice, healthcare, welfare, and education (e.g "high stakes" domains) should no longer use'black box' AI and algorithmic systems." The remaining recommendations deal with operational details, like examining training data for bias and validating the performance of the models to ensure that they aren't misfiring; and areas where work needs to be done, like evaluation of the impact of AI on hiring and HR, setting data-set quality standards; bringing cross-disciplinary expertise to bias evaluation; and the active inclusion of women, minorities and other marginalized populations in systems design and evaluation. This includes the unreviewed or unvalidated use of pre-trained models, AI systems licensed from third party vendors, and algorithmic processes created in-house. The use of such systems by public agencies raises serious due process concerns, and at a minimum such systems should be available for public auditing, testing, and review, and subject to accountability standards.