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Press room • • • • • Press Releases AutoMapa Android is the highest selling product in Google Play! 8/3/2012 In less than 48 hours after the debut of its pre-production version, AutoMapa Android generated the highest sales on the Polish Google Play website!
AutoMapa was one of the most highly anticipated applications in Google Play. The premiere of the Release Candidate version electrified the Android community, and in less than 48 hours after its debut, AutoMapa became the highest selling application on the Polish Google Play website! AutoMapa Android offers the most effective combination of off-line maps and on-line traffic data for the little green robot. Maps are available at all times, including when there is no GSM or Wi-Fi coverage. They can be used throughout Poland and Europe at no additional charge. Priced at PLN 4.99, the AutoMapa Android Starter provides access to all programme functions for 7 days, including the LiveDrive!
Technology which supports navigation based on updated traffic information. When the starter expires, users can buy a license for 7 days (PLN 19.99), 90 days (PLN 59.99) or one year (PLN 119.99). During the final testing stage of AutoMapa Android planned in the coming days, the prices will be reduced to only PLN 4.99 (1/4 of the regular price) for a 7-day license and PLN 19.99 (1/3 of the regular price) for a 90-day license. Licenses purchased during the testing stage will remain valid after the release of the final product. The map browser and the full Point of Interest (POI) database will be available after the subscription expires.
Jan 23, 2013 - Posted by Richard Salgado, Legal Director, Law Enforcement and Information Security Today we're releasing new data for the Transparency.
AutoMapa Android Release Candidate is available from the Google Play store and at.
Jul 13, 2018 - An iceberg six kilometres wide has broken off from a glacier in eastern Greenland and scientists have captured the dramatic event on video. Dec 21, 2018 AutoMapa Android lets you avoid traffic jams and other disruptions on Polish roads with LiveDrive! The starting package offers 7-day navigation in Poland and Europe plus map and POI browsing without time limits.
From smartphone assistants to image recognition and translation, machine learning already helps us in our everyday lives. But it can also help us to tackle some of the world’s most challenging physical problems -- such as energy consumption.
Large-scale commercial and industrial systems like data centres consume a lot of energy, and while much has been done to, there remains a lot more to do given the world’s increasing need for computing power. Reducing energy usage has been a major focus for us over the past 10 years: we have built our own at Google, invented and invested heavily in, with the goal of being powered 100 percent by renewable energy.
Compared to five years ago, we now get around 3.5 times the computing power out of the same amount of energy, and we continue to make many improvements each year. Major breakthroughs, however, are few and far between -- which is why we are excited to share that by applying DeepMind’s machine learning to our own Google data centres, we’ve managed to reduce the amount of energy we use for cooling by up to 40 percent. In any large scale energy-consuming environment, this would be a huge improvement. Given how sophisticated Google’s data centres are already, it’s a phenomenal step forward. The implications are significant for Google’s data centres, given its potential to greatly improve energy efficiency and reduce emissions overall. This will also help other companies who run on Google’s cloud to.
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While Google is only one of many data centre operators in the world, many are not powered by renewable energy as we are. Every improvement in data centre efficiency reduces total emissions into our environment and with technology like DeepMind’s, we can use machine learning to consume less energy and help address one of the biggest challenges of all -- climate change. One of the primary sources of energy use in the data centre environment is cooling. Just as your laptop generates a lot of heat, our data centres -- which contain servers powering Google Search, Gmail, YouTube, etc. -- also generate a lot of heat that must be removed to keep the servers running. This cooling is typically accomplished via large industrial equipment such as pumps, chillers and cooling towers.
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However, dynamic environments like data centres make it difficult to operate optimally for several reasons: • The equipment, how we operate that equipment, and the environment interact with each other in complex, nonlinear ways. Traditional formula-based engineering and human intuition often do not capture these interactions. • The system cannot adapt quickly to internal or external changes (like the weather). This is because we cannot come up with rules and heuristics for every operating scenario. • Each data centre has a unique architecture and environment.