Uncle Sam is padding the Treasury with millions of dollars to assess bots at the same time that corporations invest more in advanced technology and labor-saving machinery, according to experts. New "robot" taxes are expected to multiply in the coming decades as millions of Americans see their jobs automated away. "Yes, governments already tax robots because they tax virtually everything that goes into developing and making robots," economist and author Mark Thornton told The Post. "In a few cases, there are subsidies such as government grants for robot development. But that still means they are taxing you and me to provide the subsidies." Taxing robots -- a proposal first suggested by Microsoft founder Bill Gates in 2017 as a way for government to tame the inexorable ascent of machines, and to finance new programs like elder care and education -- is back on the front burner.
The push over the last decade by international maritime ports to fully automate operations has sparked the ire of many U.S. longshoremen whose high-paying jobs and way of life are at stake. The trend also sets up a battle between their unions and companies and governments who see automation as a cleaner, more efficient and more cost-friendly alternative to the current system. "This may be the most difficult and complex challenge we've ever undertaken,'' Dan Sperling, professor of civil engineering and environmental science at the University of California, Davis and a member of California's Air Resources Board, told Bloomberg. "We're trying to change the entire freight system.'' California is on the frontlines in the battle over automation as the ports of Long Beach, Los Angeles and Oakland handle 40 percent of U.S. container traffic and that number is expected to increase with the expansion of the Panama Canal.
School of Information Technology, Deakin University, Geelong, Australia Robots are increasingly tested in public spaces, towards a f uture where urban environments are not only for humans but for autonomous syst ems. While robots are promising, for convenience and efficiency, there are challenges associated with building cities crowded with machines. This p aper provides an overview of the problems and some solutions, and calls for gr eater attention on this matter . Urban environments will increasingly be spaces for autonom ous systems, of which automated vehicles is only one popular type. Robot wheelchairs could be used in public as well other robot -transporters to help the elderly.
Lamp lighters once performed a vital service for Londoners. Every evening as dusk fell they lit the gas lamps that illuminated the city's shadowy streets, returning just before dawn to extinguish the flames. It was a respectable job, often passed from father to son. But, apart from the small band of British Gas engineers who maintain the 1,500 gas lamps still clustered around the royal parks, Westminster and Covent Garden, lamp lighters are now a thing of the past, their jobs snuffed out by automated timers and electricity. The lamp lighters are part of a wider narrative that shapes every city: technological change.
The rise of data plumbing, to make big data run smoothly, safely, reliably, and fast through all "data pipes" (Internet, Intranet, in-memory, local servers, cloud, Hadoop clusters etc.), optimizing redundancy, load balance, data caching, data storage, data compression, signal extraction, data summarization and more. We bought the domain name DataPlumbing.com The rise of the data plumber, system architect, and system analyst (a new breed of engineers and data scientists), a direct result of the rise of data plumbing Use of data science in unusual fields such as astrophysics, and the other way around (data science integrating techniques from these fields) The rise of the right-sized data (as oppose to big data). Other keywords related to this trend is "light analytics", big data diet", "data outsourcing", the re-birth of "small data". Not that big data is going away, it is indeed getting bigger every second, but many businesses are trying to leverage an increasingly smaller portion of it, rather than being lost in a (costly) ocean of unexploited data.