Automation will soon eliminate millions upon millions of jobs, and while new jobs will certainly be created, it is unclear whether people will be able to learn the necessary new skills fast enough. Suppose you are a fifty-years-old truck driver, and you just lost your job to a self-driving vehicle. Now there are new jobs in designing software or in teaching yoga to engineers – but how does a fifty-years-old truck driver reinvent himself or herself as a software engineer or as a yoga teacher? And people will have to do it not just once but again and again throughout their lives, because the automation revolution will not be a single watershed event following which the job market will settle down, into a new equilibrium. Rather, it will be a cascade of ever bigger disruptions, because AI is nowhere near its full potential.
The first big investment wave in tech was the personal computer. Then came software, the internet, smartphones, social media and cloud computing. The next big thing is artificial intelligence, or AI, professional stock pickers say. AI is the science-fiction-like technology in which computers are programmed to think and perform the tasks ordinarily done by humans. The size of the global AI market is expected to grow to $202.6 billion by 2026, up from $20.7 billion in 2018, according to Fortune Business Insights.
Artificial Intelligence is already impacting Manufacturing, Retail, Marketing, Healthcare, Food industries and more. Today we will take an in-depth look at another industry, that with proper AI expertise from development companies could be disrupted. Transportation is an industry that helps humanity with moving people their belongings from one location to the other. While doing that, this industry had experienced countless twists, turns, breakthroughs, and setbacks to get to the place where it is now. The year 1787 was the defining one for this industry because steamboat was introduced and changed everything.
Truly "autonomous" systems are starting to replace or augment many of the routine tasks and processes people perform every day, improving efficiency while freeing individuals for higher-level pursuits. But what's often overlooked is how much progress is happening in other areas and industries: healthcare, air travel, energy provision, retail, logistics, agriculture, and construction. Autonomous systems are even helping governments match refugees with the most suitable communities to live, as detailed in one of the four real-world vignettes we present below. Such optimism makes sense, given advances such as self-managing and self-patching databases in IT. But our survey's other findings might underestimate the pace of change: Just 24% say they expect to see significant use of autonomous tech in construction, for example, even though self-driving bulldozers already are in use on select projects.
Nearly half of UAE residents are likely to own a self-driving car in the next five years if it are available to them, according to a new survey. The poll by YouGov also showed that close to a quarter (23 percent) are unlikely to do so and an equal proportion is unsure. It said men are more inclined to own an autonomous car in the future than women, with 53 percent of males expressing interest compared to 42 percent of females respondents. Among the various age-groups, people in their thirties (52 percent) are more likely than those under 30 (47 percent) and those aged 40 and above (48 percent) to possess one. When it comes to safety, YouGov's research showed that 43 percent feel driverless cars are safer than human-driven cars, 27 percent think they are less safe while 17 percent say they are just about the same.
A model invented by researchers at MIT and Qatar Computing Research Institute (QCRI) that uses satellite imagery to tag road features in digital maps could help improve GPS navigation. Showing drivers more details about their routes can often help them navigate in unfamiliar locations. Lane counts, for instance, can enable a GPS system to warn drivers of diverging or merging lanes. Incorporating information about parking spots can help drivers plan ahead, while mapping bicycle lanes can help cyclists negotiate busy city streets. Providing updated information on road conditions can also improve planning for disaster relief.
Like the city that hosts the Consumer Electronics Show (CES) there is a lot of noise on the show floor. Sifting through the lights, sounds and people can be an arduous task even for the most experienced CES attendees. Hidden past the North Hall of the Las Vegas Convention Center (LVCC) is a walkway to a tech oasis housed in the Westgate Hotel. This new area hosting SmartCity/IoT innovations is reminiscent of the old Eureka Park complete with folding tables and ballroom carpeting. The fact that such enterprises require their own area separate from the main halls of the LVCC and the startup pavilions of the Sands Hotel is an indication of how urbanization is being redefined by artificial intelligence.
"Compared to other approaches, our non-line-of-sight imaging system provides uniquely high resolutions and imaging speeds," said research team leader Christopher A. Metzler from Stanford University and Rice University. "These attributes enable applications that wouldn't otherwise be possible, such as reading the license plate of a hidden car as it is driving or reading a badge worn by someone walking on the other side of a corner." In Optica, The Optical Society's journal for high-impact research, Metzler and colleagues from Princeton University, Southern Methodist University, and Rice University report that the new system can distinguish submillimeter details of a hidden object from 1 meter away. The system is designed to image small objects at very high resolutions but can be combined with other imaging systems that produce low-resolution room-sized reconstructions. "Non-line-of-sight imaging has important applications in medical imaging, navigation, robotics and defense," said co-author Felix Heide from Princeton University.
Are you sure you want to view these Tweets? Agreed, and appreciate the parallel drawn here. Definitely a huge challenge to regulate these emerging & booming sectors. Interesting reading this as well: «I have been proud to work with #Tesla on advancing cleaner, more #sustainable #transportation technologies. Impact of #Digitalization and #Automation, #futureofwork "This is your #pilot speaking.
Japanese railway companies are turning to artificial intelligence to help tackle potential problems for their shinkansen bullet trains caused by accumulations of snow. West Japan Railway Co. is developing an AI system to gauge the amount of snow attached to Hokuriku Shinkansen trains that cut through Niigata, Toyama and Ishikawa prefectures adjacent to the Sea of Japan. The railway operator currently decides how many personnel to deploy for snow clearance a day beforehand, based on information from meteorological data providers and past experience, but it is often not very accurate. AI will gather data from images of trains that have accumulated snow while traveling, study weather conditions and predict the number of personnel necessary for clearance work. Test operations have proved positive so far and the system is set for full introduction next winter.