Abstract: With the rapid development of AI and robotics, transporting a large swarm of networked robots has foreseeable applications in the near future. Existing research in swarm robotics has mainly followed a bottom-up philosophy with predefined local coordination and control rules. However, it is arduous to verify the global requirements and analyze their performance. This motivates us to pursue a top-down approach, and develop a provable control strategy for deploying a robotic swarm to achieve a desired global configuration. Specifically, we use mean-field partial differential equations (PDEs) to model the swarm and control its mean-field density (i.e., probability density) over a bounded spatial domain using mean-field feedback.

Abstract: Perceiving 3D objects from monocular inputs is crucial for robotic systems, given its economy compared to multi-sensor settings. It is notably difficult as a single image can not provide any clues for predicting absolute depth values. Motivated by binocular methods for 3D object detection, we take advantage of the strong geometry structure provided by camera ego-motion for accurate object depth estimation and detection. We first make a theoretical analysis on this general two-view case and notice two challenges: 1) Cumulative errors from multiple estimations that make the direct prediction intractable; 2) Inherent dilemmas caused by static cameras and matching ambiguity. Accordingly, we establish the stereo correspondence with a geometry-aware cost volume as the alternative for depth estimation and further compensate it with monocular understanding to address the second problem.

Throughout the most recent years, as sensor and MCU costs dove and shipped volumes have gone through the roof, an ever-increasing number of organizations have attempted to exploit by adding sensor-driven embedded AI to their products. Automotive is driving the trend– the average non-autonomous vehicle presently has 100 sensors, sending information to 30-50 microcontrollers that run about 1m lines of code and create 1TB of data per vehicle every day. Extravagance vehicles may have twice the same number of, and autonomous vehicles increase the sensor check significantly more drastically. Industrial equipment is turning out to be progressively "brilliant" as creators of rotating, reciprocating and other types of equipment rush to add usefulness for condition monitoring and predictive support, and a huge number of new consumer products from toothbrushes, to vacuum cleaners, to fitness monitors add instrumentation and "smarts". An ever-increasing number of smart devices are being introduced each month. We are now at a point where artificial intelligence and machine learning in its exceptionally essential structure has discovered its way into the core of embedded devices.

Naheed Kurji is the President and CEO of Cyclica, a Toronto-based biotechnology company that leverages artificial intelligence and computational biophysics to reshape the drug discovery process. Cyclica leverages artificial intelligence and computational biophysics to reshape the drug discovery process. Can you discuss in what way AI is used in this process? Technology has played a critical role in drug discovery dating back to the '80s. However, the drug discovery and development process is still very inefficient, time consuming and expensive, costing more than 2 billion dollars over 12 years.

University of Arizona researchers are collaborating on an autonomous technology project that could prove autonomous vehicles can improve traffic flow and decrease fuel consumption. The project aims to demonstrate for the first time in real traffic that using intelligent control of a small number of connected and automated vehicles can improve the energy efficiency of all the vehicles by reducing traffic congestion, said Electrical and Computer Engineering (ECE) Professor Jonathan Sprinkle. "More and more passenger vehicles come with features that automate some driving tasks," Sprinkle said. "New advancements in machine learning are showing how small changes to those features can work to address societal-scale challenges, such as the amount of fuel spent while sitting in stop-and-go traffic during a daily commute." The project is being funded through a $3.5 million U.S. Department of Energy cooperative research project.

Ping Identity, the leader in Identity Defined Security, announced that it has made several significant updates to PingIntelligence for APIs, its AI-powered API cybersecurity solution. These latest enhancements include an AI-based cloud trial, the ability to detect new types of attacks, support for Splunk environments, and additional integration with API gateways. "As evidenced by the new advancements to our PingIntelligence for APIs solution, we're committed to delivering even more leading-edge technology to protect our customers' API infrastructures against these emerging threats." The lack of visibility into how APIs are consumed is becoming commonplace in today's enterprise environment. In fact, a recent Ping Identity survey conducted among security and IT professionals reveals that 45% of respondents aren't confident in their organization's ability to detect whether a bad actor is accessing their APIs.

Bill Ford Jr., executive chairman of Ford Motor Co., recognizes the automotive industry is on the verge of mutation and wants his 114-year old legacy company to remain a top performer. Speaking to Detroit Economic Club members Tuesday at Ford Field in Detroit, Ford said every aspect of the automotive business model is being disrupted by new technologies. "Every single thing is changing; from what's propelling cars, to the ownership model to artificial intelligence, 3-D printing ... autonomous driving ... even the way we finance," Ford said. Great fortunes will be made in this era." Ford said the "race" to autonomous driving and mobility is so often focused on the next technology advancement that the companies are missing the sole purpose of those advancements: people. "This is all about people," he said. "It's not who is first to market, but who is most thoughtful to market.