MOUNTAIN VIEW, Calif.—On May 18, the first day of Google I/O 2016, Google brought to the Shoreline Amphitheater stage news involving its Android mobile operating system, unveiled a powerful analytics engine and introduced a new server ASIC at the same time.
Yes, Google not only creates software of all kinds, it also makes server components. In fact, it’s been building its own servers, networks and storage facilities for as long as it’s been in business, which is just shy of two decades.
Here’s a rundown of what Google announced for software developers on May 18.
Android, currently being pounded by Oracle in federal-level copyright litigation up the 101 freeway in San Francisco, is morphing into its next version, called “N.”
“In Android N, we want to achieve a new level of product excellence for Android, so we’ve carried out some pretty deep surgery to the platform, rewriting and redesigning some fundamental aspects of how the system works,” Google Android Vice President of Engineering Dave Burke said.
“For Android N, we are focused on three key themes: performance, productivity and security. The first Developer Preview introduced a brand new JIT compiler to improve software performance, make app installs faster and take up less storage. The second N Developer Preview included Vulkan, a new 3D-rendering API to help game developers deliver high performance graphics on mobile devices.”
Both previews also brought useful productivity improvements to Android, including Multi-Window support and Direct Reply, Burke said.
Android N also adds some important new features to help keep users safer and more secure, Burke said.
“Inspired by how Chromebooks apply updates, we’re introducing seamless updates so that new Android devices built on N can install system updates in the background,” Burke said. “This means that the next time a user powers up his device, new devices can automatically and seamlessly switch into the new updated system image.
“Today’s release of Android N Developer Preview 3 is our first beta-quality candidate, available to test on your primary phone or tablet,” Burke said.
The Firebase Analytics engine on the Google Cloud Platform is a free and unlimited analytics solution providing developers with unlimited reporting for up to 500 distinct events that can be defined using the Firebase SDK (software development kit).
Firebase Analytics reports helps users understand how users behave, which enables informed decisions regarding app marketing and performance optimizations.
“One of the most requested features by Firebase developers is the ability to store images, videos and other large files,” product manager James Tamplin wrote in his blog. “The new Firebase Storage is powered by Google Cloud Storage, giving it massive scalability and allowing stored files to be easily accessed by other projects running on Google Cloud Platform.
“Firebase now uses the same underlying account system as GCP, which means you can use any GCP product with your Firebase app. For example, you can export raw analytics data from the new Firebase Analytics to Google BigQuery to help you surface advanced insights about your application and users.”
Firebase is slated to be a freely available component for all Android development in the future, Google said.
Google Releases Android N, Firebase Analytics, New ASIC
Tensor Processing Unit (TPU)
The company also introduced a new chipset called Tensor Processing Unit (TPU), a custom application-specific integrated circuit (ASIC) for machine learning that fits in the same footprint of a hard drive.
(TPUs) are custom ASICs Google built specifically for machine learning—and tailored for TensorFlow, an open-source library for machine learning. Google has been running TPUs inside its data centers for more than a year and has found them to deliver an order of magnitude-better optimized performance per watt for machine learning, Urs Hölzle, Google’s senior vice president for technical infrastructure, told reporters.
This is roughly equivalent to fast-forwarding technology about seven years into the future (three generations of Moore’s Law). TPUs are tailored to machine-learning applications, allowing the chip to be more tolerant of reduced computational precision, which means it requires fewer transistors per operation. Because of this, TPUs can squeeze more operations per second into the silicon, use more sophisticated and powerful machine-learning models and apply these models more quickly, so users get more intelligent results more rapidly.
A board with a TPU fits into a hard disk-drive slot in Google’s data center racks.
“TPUs are used alongside regular CPUs,” Hölzle said at an invitation-only press conference. “They’re not designed to be the lead processor for anything.”
TPUs were the secret sauce for AlphaGo in its recent intelligence challenge match in South Korea.
AlphaGo versus Lee Sedol, or Google DeepMind Challenge Match, was a five-game Go match between South Korean professional Go player Lee Sedol and AlphaGo, a computer Go program developed by Google DeepMind. The match was played in Seoul, South Korea, March 9-15. AlphaGo won all but the fourth game; all games were won by resignation. The match has been compared with the historic chess match between Deep Blue and Garry Kasparov in 1997.
New APIs for Sheets, Slides and Classroom
Google also announced three new APIs for Sheets, Slides and Classroom that enable developers to build feature-rich integrations to help users be more productive using all their business apps.
—Sheets API gives developers programmatic access to nearly all of the features users can add to a spreadsheet;
—Slides API enables developers to export business data from their apps, allowing users to generate and update content and visuals in slide decks; and
— Classroom API adds coursework endpoints that allow developers to sync grades and assignment data between Google Classroom and their applications.
“The new Sheets API, available today, gives developers programmatic access to powerful features in the Sheets web and mobile interfaces, including charts and pivot tables,” Sheets Product Manager Tom Holman wrote in his blog.
“For example, developers can use Sheets as part of a rich workflow that pushes data from their app into Sheets and allows users to collaborate on that data before the updated data is pulled back into the original app, removing altogether the need to copy and paste,” he wrote.