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.
The connectivity benefits of 5G are expected to make businesses more competitive and give consumers access to more information faster than ever before. Connected cars, smart communities, industrial IoT, healthcare, immersive education--they all will rely on unprecedented opportunities that 5G technology will create. The enterprise market opportunity is driving many telecoms operators' strategies for, and investments in, 5G. Companies are accelerating investment in core and emerging technologies such as cloud, internet of things, robotic process automation, artificial intelligence and machine learning. IoT (Internet of Things), as an example, improving connectivity and data sharing between devices, enabling biometric based transactions; with blockchain, enabling use cases, trade transactions, remittances, payments and investments; and with deep learning and artificial intelligence, utilization of advanced algorithms for high personalization.
Drone racing is an increasingly popular sport with big money prizes for skilled professionals. New control algorithms developed at the University of Zurich (UZH) have beaten experienced human pilots for the first time – but they still have significant limitations. In the past, attempts to develop automated algorithms to beat humans have run into problems with accurately simulating the limitations of the quadcopter and the flight path it takes. Traditional flight paths around a complex drone racing course are calculated using polynomial methods which produce a series of smooth curves, and these are not necessarily as fast as the sharper and more jagged paths flown by human pilots. A team from the Robotics and Perception Group at UZH has developed a trajectory planning algorithm to calculates the optimal route at every point in the flight, rather than doing it section by section.
It's one thing to have your cabbage patch or running man shown up by Zoomers on TikTok, but it's another level of embarrassment to have a robot out dance you. That's exactly what Boston Dynamics' cohort of robots -- including its dog Spot and more human-like bot Atlas -- did in a video that resurfaced on Twitter this weekend. Swaying to the tune of the 1962 classic "Do You Love Me?" by the Contours, the robotic dance team inspired awe, disbelief, and dread in users. But while online lamenting over the robot apocalypse is nearly always tongue-in-cheek, the engineering achievement lurking behind Spot's dance moves means this reality could be much closer and darker than we realize. It is difficult to believe your eyes when you watch the Boston Dynamics robots bust a move -- albeit jerkily -- in the December 2020 video that made new Twitter rounds this weekend.
Technology is continuously updating at such a fast pace which it is might be quicker than light. A programming language that is making the rounds today might be obsolete by the next couple of days. As more money is invested in the development and research, professionals and computing scientists are continuously tweaking and enhancing current technologies to maximize them. Thus, new technologies and programming language, patch, library, and plug-in are released per hour. To maintain this fast pace of development, you need to keep on knowing the newest technology ideas.
Due to the recent adaptive quarantine measures imposed in virtually all parts of the world, air travel, public transportation, and many other sectors took a really big hit in 2020. However, the automotive world and autonomous vehicles, in particular, have shown increased resilience during this difficult time. In fact, companies like Ford have increased their investments in the development of electric and self-driving cars by allocating $29 billion dollars in the fourth quarter of last year. Specifically, $7 billion of that money will go towards the development of self-driving cars. So Ford is joining General Motors, Tesla, Baidu, and other automakers in heavily investing in autonomous vehicles.
There may not have been any fans in the Olympic Stadium, but Japan still found a way to put on a show for the opening of the 2020 Summer Games. The host country charmed early with the parade of nations, which featured an orchestrated video game soundtrack, and then showed off the type of creativity it's known for with a performance involving the Olympic pictograms. But Tokyo saved the biggest spectacle for last. Towards the end of the ceremony, a fleet of 1,824 drones took to the skies above the Olympic Stadium. Initially arrayed in the symbol of the 2020 Games, they then took on the shape of the Earth before a rendition of John Lenon's "Imagine," which was reworked by Hans Zimmer for the Olympics, played across the stadium.
The pace at which technology is continuously evolving is unprecedented. Each and every day seemingly brings with it some new and exciting thing to be excited about in the world of tech. Fresh off a year that saw the world retreat indoors in an effort to curb the spread of the COVID-19 virus, much of society grew more reliant and more accepting of technology as a whole. Technology played a big role in various aspects of everyday life such as communication, data transfer, analysis, and even entertainment. More than that, in the age of digital information, a smart device is being placed in the hands of someone new every single day.
The researchers developed a method to model different levels of driver cooperativeness how likely a driver was to pull over to let the other driver pass and used those models to train an algorithm that could assist an autonomous vehicle to safely and efficiently navigate this situation. An algorithm developed by researchers at Carnegie Mellon University (CMU) could enable autonomous vehicles to navigate crowded, narrow streets where vehicles traveling in opposite directions do not have enough space to pass each other and there is no knowledge about what the other driver may do. Such a scenario requires collaboration among drivers, who must balance aggression with cooperation. The researchers modeled different levels of cooperation between drivers and used them to train the algorithm. In simulations, the algorithm was found to outperform current models; it has not yet been tested on real-world vehicles.
Alphabet's X, its R&D lab, announced Friday morning that its next big bet is in industrial robotics. Its new early-stage company Intrinsic is a robotics software and AI company that wants to help robots sense and learn, thereby making them more adaptable to different environments. "The surprisingly manual and bespoke process of teaching robots how to do things, which hasn't changed much over the last few decades, is currently a cap on their potential to help more businesses," Wendy Tan-White, Intrinsic's CEO, wrote in a blog post. "Specialist programmers can spend hundreds of hours hard coding robots to perform specific jobs, like welding two pieces of metal, or gluing together an electronics case. And many dexterous and delicate tasks, like inserting plugs or moving cords, remain unfeasible for robots because they lack the sensors or software needed to understand their physical surroundings."
Alphabet has launched another company in its X moonshot factory, and this one may be its most ambitious robotics project to date. The just-opened firm, Intrinsic, plans to make industrial robots more accessible to people and businesses that couldn't otherwise justify the effort involved to teach the machines. You could see robotic manufacturing in more countries, for example, or small businesses that can automate production that previously required manual labor. Intrinsic will focus on software tools that make these robots easier to use, more flexible and more affordable. To that end, the company has been testing a mix of software tools that include AI techniques like automated perception, motion planning and reinforcement learning.