To achieve 98 days total above Peru, the balloon made nearly 20,000 adjustments. Google's new wind-predicting algorithms have kept one of its internet-beaming air balloons aloft in Peru's airspace for a total of 98 days. Google's measure for success when it comes to Project Loon isn't just keeping balloons flying for 100 days, but ensuring they're not carried out to sea by air currents where they can't deliver wireless internet to the public. Project Loon, which sits in the X unit of Google's parent Alphabet, has used human-coded algorithms to determine how high or low in the stratosphere the air balloons need to be to catch a current that will take them in the desired direction. However, as Wired reports, updates to Loon's navigational system apply machine-learning techniques to the roughly 17 million kilometers of flight data it's collected to predict wind directions at different altitudes.
This summer, the Google X lab launched a balloon into the stratosphere over Peru, and it stayed there for 98 days. Launching balloons into the stratosphere is a usual thing for the Google X lab--or just X, as it's now called after spinning off from Google and nestling under the new umbrella called Alphabet. X is home to Project Loon, an effort to beam the Internet from the stratosphere down to people here on Earth. The hope is that these balloons can fly over areas of the globe where the Internet is otherwise unavailable and stay there long enough to provide people with a reliable connection. But there's a problem: balloons tend to float away.
Alphabet's Loon, the team responsible for beaming internet down to Earth from stratospheric helium balloons, has achieved a new milestone: its navigation system is no longer run by human-designed software. Instead, the company's internet balloons are steered around the globe by an artificial intelligence -- in particular, a set of algorithms both written and executed by a deep reinforcement learning-based flight control system that is more efficient and adept than the older, human-made one. The system is now managing Loon's fleet of balloons over Kenya, where Loon launched its first commercial internet service in July after testing its fleet in a series of disaster relief initiatives and other test environments for much of the last decade. Similar to how researchers have achieved breakthrough AI advances in teaching computers to play sophisticated video games and helping software learn how to manipulate robotic hands in lifelike ways, reinforcement learning is a technique that allows software to teach itself skills through trial and error. Obviously, such repetition is not possible in the real world when dealing with high-altitude balloons that are costly to operate and even more costly to repair in the event they crash.
Google's parent Alphabet is set to beam internet to the remotest areas of the planet via high-altitude balloons. The firm has launched six balloons as part of its'Project Loon' that have managed to transfer data across a 620-mile (1,000km) area as part of a landmark test. A spokesperson from Loon, which is a subsidiary of Alphabet, said the stratospheric balloons rely on a single connection to the ground in Nevada. The test is Project Loon's latest as it heads towards its planned commercial launch of the service next year. Google's parent Alphabet is set to beam internet into the remotest areas of the planet as part of its'Project Loon' starting next year.
Huge stratospheric balloons that act as floating cell towers in remote areas can stay in the air for hundreds of days thanks to an artificially intelligent pilot created by Google and Loon. Loon, a subsidiary of Google's parent company Alphabet, produces tennis-court-sized balloons that are filled with helium and sent into the stratosphere. Keeping these huge balloons in a fixed position is difficult as they can get blown off course. Now, researchers at Loon and Google have joined forces to create an AI controller that can counter the harsh winds of the stratosphere by releasing air to descend or adding it to ascend, riding atmospheric currents in the desired direction. The two firms used an AI technique called deep reinforcement learning to train the balloon's controllers.