Robots in the work place can perform hazardous or even 'impossible' tasks; e.g., toxic waste clean-up, desert and space exploration, and more. AI researchers are also interested in the intelligent processing involved in moving about and manipulating objects in the real world.
Weeks after a study revealed that Amazon warehouse workers are injured at higher rates than staff at rival firms, the company has revealed it's testing new robots designed to improve employee safety. The e-commerce giant has ingratiatingly named two of the bots after Sesame Street's Bert and Ernie. Bert is an Autonomous Mobile Robot (AMR) that's built to navigate through Amazon facilities. In the future, the company envisions the bot carrying large and heavy items or carts across a site, reducing the strain on its human coworkers. Ernie, meanwhile, is a workstation system that removes totes from robotic shelves and then deliveries them to employees.
In April, the European Commission released a wide-ranging proposed regulation to govern the design, development, and deployment of A.I. systems. The regulation stipulates that "high-risk A.I. systems" (such as facial recognition and algorithms that determine eligibility for public benefits) should be designed to allow for oversight by humans who will be tasked with preventing or minimizing risks. Often expressed as the "human-in-the-loop" solution, this approach of human oversight over A.I. is rapidly becoming a staple in A.I. policy proposals globally. And although placing humans back in the "loop" of A.I. seems reassuring, this approach is instead "loopy" in a different sense: It rests on circular logic that offers false comfort and distracts from inherently harmful uses of automated systems. A.I. is celebrated for its superior accuracy, efficiency, and objectivity in comparison to humans.
Artificial intelligence (AI) may be the most disruptive of all the disruptive technologies. At the very least, AI's depth and rapid evolution are fast it making it a foundation in myriad industries – a status that carries with it an assortment of investment implications. A plethora of exchange traded funds offer AI exposure in varying forms, but one of the dominant forces in that group is the ARK Autonomous Technology & Robotics ETF (CBOE: ARKQ). The actively managed ARKQ isn't a dedicated AI fund, but it features exposure to industries AI intersects with, including 3D printing, autonomous transportation, energy storage, robotics, and space exploration. As is the case with so many disruptive technologies, hardware and semiconductors are the backbones of AI, and that's not going to change anytime soon.
Did you have the chance to attend the 2021 International Conference on Robotics and Automation (ICRA 2021)? Here we bring you the papers that received an award this year in case you missed them. "An essential and challenging use case solved and evaluated convincingly. This work brings to light the artisanal field that can gain a lot in terms of safety and worker's health preservation through the use of collaborative robots. Simulation is used to design advanced control architectures, including virtual walls around the cutting-tool as well as adaptive damping that would account for the operator know-how and level of expertise."
Current advances in robotic healthcare are set to revolutionize the medical field. In recent years, there has been a significant rise in the number of autonomous robotic systems (ARS) in the field of medicine. These state-of-the-art ARS have been applied in the healthcare domain to improve outcomes in surgical operations, care of the elderly, patient rehabilitation, and assistive and companion purposes. In particular, current advances in soft robotics offer tactile human-robot interactions (HRI) which improve the safety of HRI, adaptability to wearable devices, and for use in surgical instruments such as endoscopes. The materials used in these robots and tactile interaction devices possess deformable properties which can interact safely with the body, thereby improving health outcomes and narrowing the gap between engineered systems and natural organisms.
IMAGE: Researchers explore the past, present, and future of smart vehicles and what their integration with smart cities would take. Central to any technological progress is the enrichment of human life. The internet and wireless connectivity have done that by allowing not only virtually anyone anywhere to connect real time, but by making possible connections between humans and a range of intelligent devices both indoors and outdoors, putting smart cities on the horizon. One key aspect of realizing smart cities is "smart vehicles", the latest development in intelligent transportation systems (ITS), which involve the integration of communication, mapping, positioning, network, and sensor technologies to ensure cooperative, efficient, intelligent, safe, and economical transportation. For decades, research on bringing to the streets smart vehicles that operate successfully as part of smart city infrastructure has focused on improving computing paradigms for vehicular network connectivity.
With ambitions to establish a network of autonomous trucking routes across the US, transport startup TuSimple is taking some steady and significant steps forward as it proves its technology through trials and expands into Europe. The latest test run for its self-driving trucks involved hauling a load of fresh produce over hundreds of miles across the US, where it demonstrated that it can complete such tasks in a fast and highly efficient fashion. Previously, we've seen TuSimple's Level 4 autonomous trucks use its variety of cameras and sensors to move goods as part of trials for the US Postal Service and shipping giant UPS. This time around, the startup has partnered with fresh produce provider The Giumarra Companies and Associated Wholesale Grocers to explore autonomous trucking's potential in the fresh food industry. The trial started in Nogales, Arizona, where TuSimple's truck was loaded up with fresh watermelons from Giumarra's facility.
Amid mounting claims its warehouses, especially those with robots, are unsafe, Amazon is doubling down on technology in an attempt to make them safer. The Jeff Bezos-led company is using its Amazon Robotics and Advanced Technology labs to come up with new robots to keep Amazon's warehouse workers, which make up the majority of its more than 1 million employees, safer. Robots known as'Bert' and'Ernie,' use motion-capture technology. Amazon is using technology to keep its warehouses workers safer, despite claims to the contrary. Bert was designed to navigate Amazon's warehouses independently, becoming one of the Jeff Bezos-led company's first autonomous mobile robots This allows Amazon data scientists to understand what's going on in the warehouse and apply that to a laboratory setting, before going back out to the field again.
The world today is thriving on artificial intelligence and the branch technologies associated with it. It is a truth universally acknowledged that the survival of business organizations is heavily contingent on technological advancements induced by AI integration. One such platform is Automation Anywhere that leverages AI and RPA to accelerate and empower business conductions. Automation Anywhere is a reputed global leader in robotic process automation that specializes in offering cloud-native, web-based intelligent automation solutions to empower business operations for companies. Founded in 2003, Automation Anywhere holds a strong legacy of setting benchmarks by AI and RPA adoption.
The automation industry is experiencing an explosion of growth and technology capability. To explain complex technology, we use terms such as "artificial intelligence" to convey the idea that solutions are more capable and advanced than ever before. If you are an investor, business leader, or technology user who seeks to understand the technologies you are investing in, this article is for you. What follows is an explanation of vision-guided robotics and deep-learning algorithms. That's right, the article is titled "artificial intelligence" and yet by the end of the first paragraph, we've already switched to deep-learning algorithms!