The words "fly like an eagle" are famously part of a song, but they may also be words that make some scientists scratch their heads. Especially when it comes to soaring birds like eagles, falcons and hawks, who seem to ascend to great heights over hills, canyons and mountain tops with ease. Scientists realize that upward currents of warm air assist the birds in their flight, but they don't know how the birds find and navigate these thermal plumes. To figure it out, researchers from the University of California San Diego used reinforcement learning to train gliders to autonomously navigate atmospheric thermals, soaring to heights of 700 meters--nearly 2,300 feet. The novel research results, published in the Sept. 19 issue of Nature, highlight the role of vertical wind accelerations and roll-wise torques as viable biological cues for soaring birds.
The rise of IoT has coincided with a huge amount of fear around the impact this technology will have on jobs. Arguably, the profession most in the spotlight has been drivers, as the march of autonomous vehicle technology creates an obvious challenge to the driving profession. It's a concern that need not worry those in the driving profession, at least according to a recent report commissioned by the American Center for Mobility, led by Michigan State University, and supported by the Texas A&M Transportation Institute. The report suggests that even when autonomous vehicles are a widespread presence on our roads, it will only result in a modest number of trucking jobs being impacted. The authors of this report believe that the technology will be deployed in the latter half of the 2020s, at which point some in the passenger business (taxi drivers etc.) could be affected, but they suggest that the shortage of truck drivers in the industry already, coupled with the belief that the new technology will support rather than replace drivers, lends them to believe the B2B sector won't be impacted as much.
Birds don't always flap their wings to fly; sometimes they soar by taking advantage of rising columns of warm air known as thermals. With large wingspans, they can stay aloft for hours while expending minimal energy. Exactly how they do it -- navigating tiny changes in unpredictable air currents -- isn't well-known. But scientists are now using artificial intelligence to learn their tricks, and hopefully, they can teach our aircraft to do the same. As described in a paper published this week in the journal Nature, researchers from universities in the US and Italy used machine learning to train an algorithm to control a glider to navigate thermals.
It took mankind untold eons to learn how to fly, but now artificial intelligence is doing something similar and in a fraction of the time. No, there's no robots constructing planes like the Wright brothers, but some AI-powered gliders are indeed learning how to cruise through the air just like birds, and they're getting pretty good at it. Researchers equipped a glider with an advanced algorithm and control system that allows it to navigate wind currents in the same way that birds to. By finding updrafts which help it stay aloft, the glider can slip through the air indefinitely, much like birds to when trying to minimize their energy output. The research, which was published in Nature, describes how these wind currents are used by birds.
In the crowded streets of San Francisco, companies such as Uber and Cruise Automation have been testing self-driving vehicles for years now. In suburban Phoenix, hundreds of autonomous Waymo vehicles are driving as many as 25,000 miles per day. There are, in fact, dozens of cities around the world hosting pilot programs for self-driving vehicles. The latest addition to that list is Columbus, Ohio, where a series of self-driving shuttles are being deployed on city streets this week. The electric, low-speed vehicles -- operated by the Michigan-based start-up May Mobility -- will begin testing and mapping local streets before accepting passengers in December, the company said.
Pricing science is the application of analytical techniques and methods to solve the problem of setting prices. This discipline had its origins in the development of yield management in the airline industry in the 1980s, and has since spread to many other sectors and pricing contexts, including media, retail, manufacturing, distribution, etc. The goal of B2B pricing science is to optimize pricing strategies by using prescriptive analytics to model and modify historical behavior. Although pricing science does not solely predict historical pricing behavior, predictive analytics is the foundation of this process. The first step in creating a pricing strategy, developing a robust and reliable prediction model, is crucially important because failing to understand historical behavior and failing to capture market dynamics leads to irrelevant price recommendations.
Chinese internet giant Alibaba is doubling down on its chip manufacturing with a dedicated subsidiary, co-founder and chairman Jack Ma said at an event in Hangzhou this week. The company wants to launch its first self-developed AI inference chip in the second half of 2019, supporting its move into self-driving vehicles and smart products. The move follows the company's announcement back in April that it had begun testing its own autonomous vehicle technology. China's government has been pushing to raise the standard of its home-produced chips -- particularly for use within the transport and healthcare sector -- in a bid to raise its profile as a leading tech innovator, but also to avoid over-reliance on US imports, which are continually under jeopardy due to ongoing trade tensions. Back in June, for example, President Donald Trump levied a 25 percent tariff on $50 billion worth of Chinese goods.
Once cars can finally drive themselves, we'll have more time to enjoy the journey and do other, much more interesting stuff instead. At least that's the concept behind some of the designs below, developed by retail giant IKEA's "future living lab," SPACE10, based in Copenhagen. SPACE10 was asked to come up with designs for autonomous vehicles that would be extensions of our homes, offices, and local institutions. Some of the agency's seven ideas, shown below, are almost practical. Who can't imagine autonomously driven cafés or pop-up stores?
It's hard to believe how quickly the future is approaching. Waymo, formerly the Google Self-Driving Car Project, plans to launch its first commercial service for self-driving cars later this year, essentially a fully automated ride-hailing service covering about 100 square miles in Phoenix, Arizona. The company is called Navya, and its two self-driving cars currently on sale include the Autonom Shuttle and the smaller Autonom Cab. Both run on fully electric power, and while the top speed is 55 mph the vehicles are intended for urban environments only where maximum speeds reached are only around 30 mph.