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Pervasive AI for IoT Applications: Resource-efficient Distributed Artificial Intelligence

arXiv.org Artificial Intelligence

Artificial intelligence (AI) has witnessed a substantial breakthrough in a variety of Internet of Things (IoT) applications and services, spanning from recommendation systems to robotics control and military surveillance. This is driven by the easier access to sensory data and the enormous scale of pervasive/ubiquitous devices that generate zettabytes (ZB) of real-time data streams. Designing accurate models using such data streams, to predict future insights and revolutionize the decision-taking process, inaugurates pervasive systems as a worthy paradigm for a better quality-of-life. The confluence of pervasive computing and artificial intelligence, Pervasive AI, expanded the role of ubiquitous IoT systems from mainly data collection to executing distributed computations with a promising alternative to centralized learning, presenting various challenges. In this context, a wise cooperation and resource scheduling should be envisaged among IoT devices (e.g., smartphones, smart vehicles) and infrastructure (e.g. edge nodes, and base stations) to avoid communication and computation overheads and ensure maximum performance. In this paper, we conduct a comprehensive survey of the recent techniques developed to overcome these resource challenges in pervasive AI systems. Specifically, we first present an overview of the pervasive computing, its architecture, and its intersection with artificial intelligence. We then review the background, applications and performance metrics of AI, particularly Deep Learning (DL) and online learning, running in a ubiquitous system. Next, we provide a deep literature review of communication-efficient techniques, from both algorithmic and system perspectives, of distributed inference, training and online learning tasks across the combination of IoT devices, edge devices and cloud servers. Finally, we discuss our future vision and research challenges.


Drones With 'Most Advanced AI Ever' Coming Soon To Your Local Police Department

#artificialintelligence

Three years ago, Customs and Border Protection placed an order for self-flying aircraft that could launch on their own, rendezvous, locate and monitor multiple targets on the ground without any human intervention. In its reasoning for the order, CBP said the level of monitoring required to secure America's long land borders from the sky was too cumbersome for people alone. To research and build the drones, CBP handed $500,000 to Mitre Corp., a trusted nonprofit Skunk Works that was already furnishing border police with prototype rapid DNA testing and smartwatch hacking technology. They were "tested but not fielded operationally" as "the gap from simulation to reality turned out to be much larger than the research team originally envisioned," a CBP spokesperson says. This year, America's border police will test automated drones from Skydio, the Redwood City, Calif.-based startup that on Monday announced it had raised an additional $170 million in venture funding at a valuation of $1 billion. That brings the total raised for Skydio to $340 million.


Drones With 'Most Advanced AI Ever' Coming Soon To Your Local Police Department

#artificialintelligence

Three years ago, Customs and Border Protection placed an order for self-flying aircraft that could launch on their own, rendezvous, locate and monitor multiple targets on the ground without any human intervention. In its reasoning for the order, CBP said the level of monitoring required to secure America's long land borders from the sky was too cumbersome for people alone. To research and build the drones, CBP handed $500,000 to Mitre Corp., a trusted nonprofit Skunk Works that was already furnishing border police with prototype rapid DNA testing and smartwatch hacking technology. They were "tested but not fielded operationally" as "the gap from simulation to reality turned out to be much larger than the research team originally envisioned," a CBP spokesperson says. This year, America's border police will test automated drones from Skydio, the Redwood City, Calif.-based startup that on Monday announced it had raised an additional $170 million in venture funding at a valuation of $1 billion. That brings the total raised for Skydio to $340 million.


Drones With 'Most Advanced AI Ever' Coming Soon To Your Local Police Department

#artificialintelligence

Three years ago, Customs and Border Protection placed an order for self-flying aircraft that could launch on their own, rendezvous, locate and monitor multiple targets on the ground without any human intervention. In its reasoning for the order, CBP said the level of monitoring required to secure America's long land borders from the sky was too cumbersome for people alone. To research and build the drones, CBP handed $500,000 to Mitre Corp., a trusted nonprofit Skunk Works that was already furnishing border police with prototype rapid DNA testing and smartwatch hacking technology. They were "tested but not fielded operationally" as "the gap from simulation to reality turned out to be much larger than the research team originally envisioned," a CBP spokesperson says. This year, America's border police will test automated drones from Skydio, the Redwood City, Calif.-based startup that on Monday announced it had raised an additional $170 million in venture funding at a valuation of $1 billion.


Machine Learning-Based Automated Design Space Exploration for Autonomous Aerial Robots

arXiv.org Artificial Intelligence

Building domain-specific architectures for autonomous aerial robots is challenging due to a lack of systematic methodology for designing onboard compute. We introduce a novel performance model called the F-1 roofline to help architects understand how to build a balanced computing system for autonomous aerial robots considering both its cyber (sensor rate, compute performance) and physical components (body-dynamics) that affect the performance of the machine. We use F-1 to characterize commonly used learning-based autonomy algorithms with onboard platforms to demonstrate the need for cyber-physical co-design. To navigate the cyber-physical design space automatically, we subsequently introduce AutoPilot. This push-button framework automates the co-design of cyber-physical components for aerial robots from a high-level specification guided by the F-1 model. AutoPilot uses Bayesian optimization to automatically co-design the autonomy algorithm and hardware accelerator while considering various cyber-physical parameters to generate an optimal design under different task level complexities for different robots and sensor framerates. As a result, designs generated by AutoPilot, on average, lower mission time up to 2x over baseline approaches, conserving battery energy.


Top 100 Artificial Intelligence Companies in the World

#artificialintelligence

Artificial Intelligence (AI) is not just a buzzword, but a crucial part of the technology landscape. AI is changing every industry and business function, which results in increased interest in its applications, subdomains and related fields. This makes AI companies the top leaders driving the technology swift. AI helps us to optimise and automate crucial business processes, gather essential data and transform the world, one step at a time. From Google and Amazon to Apple and Microsoft, every major tech company is dedicating resources to breakthroughs in artificial intelligence. As big enterprises are busy acquiring or merging with other emerging inventions, small AI companies are also working hard to develop their own intelligent technology and services. By leveraging artificial intelligence, organizations get an innovative edge in the digital age. AI consults are also working to provide companies with expertise that can help them grow. In this digital era, AI is also a significant place for investment. AI companies are constantly developing the latest products to provide the simplest solutions. Henceforth, Analytics Insight brings you the list of top 100 AI companies that are leading the technology drive towards a better tomorrow. AEye develops advanced vision hardware, software, and algorithms that act as the eyes and visual cortex of autonomous vehicles. AEye is an artificial perception pioneer and creator of iDAR, a new form of intelligent data collection that acts as the eyes and visual cortex of autonomous vehicles. Since its demonstration of its solid state LiDAR scanner in 2013, AEye has pioneered breakthroughs in intelligent sensing. Their mission was to acquire the most information with the fewest ones and zeros. This would allow AEye to drive the automotive industry into the next realm of autonomy. Algorithmia invented the AI Layer.


Who are the Visionary companies in robotics? See the 2020 SVR Industry Award winners

Robohub

These Visionary companies have a big idea and are well on their way to achieving it, although it isn't always an easy road for any really innovative technology. In the case of Cruise, that meant testing self driving vehicles on the streets of San Francisco, one of the hardest driving environments in the world. Some of our Visionary Awards go to companies who are opening up new market applications for robotics, such as Built Robotics in construction, Dishcraft in food services, Embark in self-driving trucks, Iron Ox in urban agriculture and Zipline in drone delivery. Some are building tools or platforms that the entire robotics industry can benefit from, such as Agility Robotics, Covariant, Formant, RobustAI and Zoox. The companies in our Good Robot Awards also show that'technologies built for us, have to be built by us'.


DARPA CODE Autonomy Engine Demonstrated on Avenger UAS

#artificialintelligence

General Atomics Aeronautical Systems, Inc. (GA-ASI) has demonstrated the DARPA-developed Collaborative Operations in Denied Environment (CODE) autonomy engine on the company's Avenger Unmanned Aircraft System (UAS). CODE was used in order to gain further understanding of cognitive Artificial Intelligence (AI) processing on larger UAS platforms for air-to-air targeting. Using a network-enabled Tactical Targeting Network Technology (TTNT) radio for mesh network mission communications, GA-ASI was able to demonstrate integration of emerging Advanced Tactical Data Links (ATDL), as well as separation between flight and mission critical systems. During the autonomous flight, CODE software controlled the manoeuvring of the Avenger UAS for over two hours without human pilot input. GA-ASI extended the base software behavioural functions for a coordinated air-to-air search with up to six aircraft, using five virtual aircraft for the purposes of the demonstration.


The world's biggest drone debuts, and it weighs nearly 28 tons

#artificialintelligence

A private rocket-launch startup unveiled its fully autonomous drone designed to drop a rocket in midair that shoots small satellites into orbit without a launchpad. Alabama-based company Aevum rolled out its Ravn X Autonomous Launch Vehicle at the Cecil SpacePort launch facility in Jacksonville, Fla., on Thursday. America is changing faster than ever! Add Changing America to your Facebook or Twitter feed to stay on top of the news. The 80-foot aircraft has a wingspan of 60 feet, stands 18 feet tall and is the world's largest Unmanned Aircraft System (UAS) by mass, weighing 55,000 pounds.


AI-Powered Sensing Technology to be Developed for MQ-9 UAS

#artificialintelligence

General Atomics Aeronautical Systems, Inc. (GA-ASI) has been awarded a contract by the U.S. Department of Defense's Joint Artificial Intelligence Center (JAIC) to develop enhanced autonomous sensing capabilities for unmanned aerial vehicles (UAVs). The JAIC Smart Sensor project aims to advance drone-based AI technology by demonstrating object recognition algorithms and employing onboard AI to automatically control UAV sensors and direct autonomous flight. GA-ASI will deploy these new capabilities on a MQ-9 Reaper UAV equipped with a variety of sensors, including GA-ASI's Reaper Defense Electronic Support System (RDESS) and Lynx Synthetic Aperture Radar (SAR). GA-ASI's Metis Intelligence, Surveillance and Reconnaissance (ISR) tasking and intelligence-sharing application, which enables operators to specify effects-based mission objectives and receive automatic notification of actionable intelligence, will be used to command the unmanned aircraft. J.R. Reid, GA-ASI Vice President of Strategic Development, commented: "GA-ASI is excited to leverage the considerable investment we have made to advance the JAIC's autonomous sensing objective. This will bring a tremendous increase in unmanned systems capabilities for applications across the full-range of military operations."