It's Monday morning and you're in Hong Kong having coffee with your new boss, a virtual robot powered by artificial intelligence. Meanwhile, your digital clone is attending another meeting on your behalf, taking notes that you'll review later, but you're actually working from your bedroom in Rio de Janeiro. It may sound straight out of a science fiction novel, but this is the future of work promised by the metaverse and by NetDragon, a Chinese company that recently appointed an AI-powered virtual humanoid robot as the rotating CEO of its flagship subsidiary, Fujian NetDragon Websoft. The metaverse, often dubbed the next version of the Internet, promises a 3D virtual world that people enter via virtual reality (VR) and augmented reality (AR) headsets to do business, hang out and play games through their virtual avatars or holograms. NetDragon Websoft, the Chinese gaming company which has gained a reputation with games such as Eudemons Online, Heroes Evolved, Conquer Online and Under Oath, is betting heavily on this new digital world and its related technologies.

Machine vision technology helps factory computers recognise objects with greater accuracy and reliability, and in many cases has replaced quality inspection performed by humans. But that's not the end of the story, because advanced automation technologies like machine vision can be further enhanced with the addition of machine learning, according to a report by technology market research firm ARC Advisory Group. Machine vision systems provide object recognition capabilities and have demonstrated their cost effectiveness in inspection, measurement, scanning and object detection in manufacturing by improving consistency, productivity and overall quality. However, an underlying limitation is that these systems are generally developed to handle a limited number of cases and they do not have the ability to train when an unexpected variation occurs, explained report author Anju Ajaykumar, analyst at ARC Advisory Group. Machine learning can help solve that problem and is already being used to build greater adaptability into machine vision systems, enabling them to understand and respond appropriately to manufacturing variations.

Artificial intelligence, augmented reality and virtual reality are here to stay, but what impact will they have on jobs and training? A new study by Pew Research Center and Elon University's Imagining the Internet Center asked more than 1,400 technologists, futurists and scholars whether well-prepared workers be able to keep up in the race with artificial intelligence tools, and what impact this development will have on market capitalism. According to Elon University, most of the experts said they hope to see education and jobs-training ecosystems shift in the next decade to exploit liberal arts-based critical-thinking-driven curriculums; online courses and training amped up by artificial intelligence, augmented reality and virtual reality; and scaled-up apprenticeships and job mentoring. However, some expressed fears that education will not meet new challenges or -- even if it does -- businesses will implement algorithm-driven solutions to replace people in many millions of jobs, leading to a widening of economic divides and capitalism undermining itself. "The vast majority of these experts wrestled with a foundational question: What is special about human beings that cannot be overtaken by robots and artificial intelligence?" said Lee Rainie, director of internet, science and technology research at Pew Research Center and co-author of the report.

The test for what is'fair' is a matter of degree and the impression the court forms of the defendant's conduct.

Now that energy storage technologies are coming close to commercial reality, decades of work should result in artificial intelligence (AI) emerging as the third key technology in the transformation of the electricity sector. Combined with scalable generation and storage, it will blur the distinction between suppliers and consumers, with excess local generation being fed into the grid so that entities from individual homeowners to business and municipalities will become "producer-consumers" or "prosumers". Demand management systems will also have a role to play. The introduction of multiple players of widely varying consumption and production patterns connecting into a single nationwide grid is impossible until we have software able to predict and manage energy flows to ensure that supply and demand balance at all times. There are obvious drivers also for energy storage at small scale, particularly for remote locations. Apart from the potential for autonomy, and the ability to smooth draw from the grid (avoiding or at least reducing demand-based charges), local storage could relieve grid congestion and add flexibility to power generation requirements, potentially improving network stability.