The patent then goes on to describe a system that includes a gas-filled transport vehicle with a carrier compartment that could house packages and unmanned aircraft systems (UAS), known as drones. An exemplary look at the control systems of Walmart's proposed blimp, as shown in the patent Last December, an Amazon patent revealed the firm's own plan to use giant blimp-like flying warehouses to help its drones make deliveries Described as'airborne fulfilment centres' (AFC), these airships will hover over cities at 45,000 ft before releasing drones to deliver goods. 'UAVs with ordered items may be deployed from the AFC to deliver ordered items to user designated delivery locations. 'A protective device such as an airbag, foam, parachute, bumper and so forth could be used in this scenario Amazon's latest patent, called Countermeasure for Threats to an Uncrewed Autonomous Vehicle, was filed on November 17, 2014.
"We're developing self-driving technology because the world is changing rapidly," Sherif Marakby, the company's vice president of autonomous vehicles and electrification, wrote in a Medium post Tuesday morning. Marakby further opened about Ford's plans to develop self-driving cars. "We plan to develop and manufacture self-driving vehicles at scale, deployed in cooperation with multiple partners, and with a customer experience based on human-centered design principles," he wrote. "Our team has decades of experience developing and manufacturing vehicles that serve commercial operations such as taxi and delivery businesses.
"In addition to the potential impact on businesses, these trends provide a significant opportunity for enterprise architecture leaders to help senior business and IT leaders respond to digital business opportunities and threats by creating signature-ready actionable and diagnostic deliverables that guide investment decisions." The Hype Cycle for Emerging Technologies report is the longest-running annual Gartner Hype Cycle, providing a cross-industry perspective on the technologies and trends that business strategists, chief innovation officers, R&D leaders, entrepreneurs, global market developers and emerging-technology teams should consider in developing emerging-technology portfolios. Gartner say you need to consider the following technologies: Deep Learning, Deep Reinforcement Learning, Artificial General Intelligence, Autonomous Vehicles, Cognitive Computing, Commercial UAVs (Drones), Conversational User Interfaces, Enterprise Taxonomy and Ontology Management, Machine Learning, Smart Dust, Smart Robots and Smart Workspace. They have a long list of technologies to consider under immersive experiences, including: 4D Printing, Augmented Reality (AR), Computer-Brain Interface, Connected Home, Human Augmentation, Nanotube Electronics, Virtual Reality (VR) and Volumetric Displays.
In order to decipher these complex situations, autonomous vehicle developers are turning to artificial neural networks. In place of traditional programming, the network is given a set of inputs and a target output (in this case, the inputs being image data and the output being a particular class of object). The process of training a neural network for semantic segmentation involves feeding it numerous sets of training data with labels to identify key elements, such as cars or pedestrians. Machine learning is already employed for semantic segmentation in driver assistance systems, such as autonomous emergency braking, though.
Australian aged care provider, the IRT Group, has announced a world-first partnership with UK-based technology firm RDM Autonomous to develop driverless vehicles for residential aged care facilities. The Australian Ageing Agenda (AAA) reports that RDM Autonomous has recently opened its first satellite office in South Australia, and will be working with the IRT Group to bring autonomous cars to retirement homes. Details of the program will be revealed at the 2017 Information Technology in Aged Care (ITAC) Conference on the Gold Coast in late November, though the AAA reports that the companies plan to introduce RDM's Pod Zero (pictured) for initial testing at IRT's Kangara Waters facility in Canberra. Speaking with the AAA, Winston Mitchell, IRT IT project coordinator, said: "Piloting the technology on private roads within aged care communities hasn't been done before and IRT is eager to understand how driverless cars can improve residents' independence and quality of life".
Before autonomous trucks and taxis hit the road, manufacturers will need to solve problems far more complex than collision avoidance and navigation (see "10 Breakthrough Technologies 2017: Self-Driving Trucks"). These vehicles will have to anticipate and defend against a full spectrum of malicious attackers wielding both traditional cyberattacks and a new generation of attacks based on so-called adversarial machine learning (see "AI Fight Club Could Help Save Us from a Future of Super-Smart Cyberattacks"). When hackers demonstrated that vehicles on the roads were vulnerable to several specific security threats, automakers responded by recalling and upgrading the firmware of millions of cars. The computer vision and collision avoidance systems under development for autonomous vehicles rely on complex machine-learning algorithms that are not well understood, even by the companies that rely on them (see "The Dark Secret at the Heart of AI").
As its rivals get busy in developing self-driving cars, Microsoft is using Artificial Intelligence (AI) to empower autonomous gliders take decisions while they are aloft and has conducted a successful flight test in the US state of Nevada. According to a report in The New York Times late on Wednesday, Ashish Kapoor, an Indian-origin Principal Researcher at Microsoft, is leading a project in which his team tested two gliders designed to navigate the skies on their own. "Guided by computer algorithms that learned from onboard sensors, predicted air patterns and planned a route forward, these gliders could seek out thermals – columns of rising hot air – and use them to stay aloft," the report added. According to Mykel Kochenderfer, Stanford University professor of aeronautics and astronautics, Microsoft's project is a step towards self-driving vehicles "that are nimble enough to handle all the unexpected behavior that human drivers, bicyclists and pedestrians bring to public roads".
Windows introduces'Cortana': Your personal digital assistant Moon's shadow crosses from coast to coast during solar eclipse Fawn falls prey to eagle at Wisconsin's Lake Noquebay Hysterical woman is comforted'after watching Annabelle: Creation' Once completed in 2020, the factory is set to become one of the biggest buildings in the world, with a final size of 10 million square feet. 'We are still less than 30 percent done, and once complete, we expect the Gigafactory to be the biggest building in the world,' Tesla said The factory will initially produce a high performance cylindrical '2170 cell' which was jointly designed and engineered by Tesla and Panasonic to offer the best performance at the lowest production cost in an optimal form factor for both electric vehicles and energy products The factory will initially produce a high performance cylindrical '2170 cell' which was jointly designed and engineered by Tesla and Panasonic to offer the best performance at the lowest production cost in an optimal form factor for both electric vehicles and energy products. 'In 2017 alone, Tesla and Panasonic will hire several thousand local employees and at peak production, the Gigafactory will directly employ 6,500 people and indirectly create between 20,000 to 30,000 additional jobs in the surrounding regions,' said Tesla'In 2017 alone, Tesla and Panasonic will hire several thousand local employees and at peak production, the Gigafactory will directly employ 6,500 people and indirectly create between 20,000 to 30,000 additional jobs in the surrounding regions.' Windows introduces'Cortana': Your personal digital assistant Moon's shadow crosses from coast to coast during solar eclipse Fawn falls prey to eagle at Wisconsin's Lake Noquebay Hysterical woman is comforted'after watching Annabelle: Creation'
As the amount of data in the world multiplies, AI will only improve in helping us increase efficiency, save lives, reduce errors, solve complex problems and make better decisions in real time. Perhaps best known for defeating a chess master and winning the game show Jeopardy, IBM's Watson computer has also proven incredibly adept at connecting disparate pieces of information from medical journals, helping doctors save time and better treat their patients. Businesses are starting to use "voice prints" to quickly identify their customers over the phone, helping service reps save time and remove the customer frustration that comes with answering a myriad of security questions. Instead, by helping us better analyze data and make quicker, smarter decisions, it will help us realize our true potential and achieve previously unimaginable new heights.
With the rapid increases in computing power, it's easy to get seduced into thinking that raw computing power can solve problems like smart edge devices (e.g., cars, trains, airplanes, wind turbines, jet engines, medical devices). In chess, the complexity of the chess piece only increases slightly (rooks can move forward and sideways a variable number of spaces, bishops can move diagonally a variable number of spaces, etc. Now think about the number and breadth of "moves" or variables that need to be considered when driving a car in a nondeterministic (random) environment: weather (precipitation, snow, ice, black ice, wind), time of day (day time, twilight, night time, sun rise, sun set), road conditions (pot holes, bumpy, slick), traffic conditions (number of vehicles, types of vehicles, different speeds, different destinations). It's nearly impossible for an autonomous car manufacturer to operate enough vehicles in enough different situations to generate the amount of data that can be virtually gathered by playing against Grand Theft Auto.