Instant Apps now on Android™

The tech giant Google has finally started to roll out the long-awaited Instant Apps feature which simply allows the users to test the apps without installing them.

It was during the last conference I/O that the tech giant Google announced it was preparing a new set of applications for Android. These would simply waive the installation of applications on your smartphone for use.There was no date for this arrival, but the tech giant Google showed that this would be one of its priorities. For the result seems to be in sight, with the first Instant Apps arriving soon, coming from a limited group of programmers.Instant Apps are what Google understands to be a revolution in the way how mobile applications are distributed since Apple launched the iPhone and the whole concept of associated apps.

These will simply allow users to test and use the applications without having to install them, saving time and resources on their smartphone. Hence, the tech giant Google was to prepare them and announced now the first extensive tests.

Applications that are ready to be used in this new mode are still limited, but Google has supported the programmers who started testing. They will still be limited to a small group of users so that they can give concrete information on what needs to be improved and optimised.

But as normal with Google, these tests will be extended, and soon many more users will be able to test the versions of the Buzz Feed, Wish, Periscope and Wiki applications that have now been released.Any programmers who want can also develop their applications to run in this mode. These do not need to be revamped, just by changing some components will simply make the application portable.

The tech giant Google’s bet on Instant Apps is great. This will allow users to test and use new applications without having to install them on their smartphones, freeing them from the consuming resources. Instant Apps should arrive for everyone later this year (2017) for all versions of Android.

Google Launched Latest Version Android Studio 2.0 Emulator

With adaptation 2.0, as Google’s gathering item administrator for Android Studio Stephanie Cuthbertson let me know, the group needed to expand on the establishment it laid in the course of the most recent two years and spotlight on pace. “For the IDE to be delightful, it doesn’t simply need to be steady yet amazingly stable,” she let me know. The group felt that it accomplished this with the last couple of discharges.

With this overhaul, Google enormously quickened arrangement speeds, for instance. Cuthbertson lets me know that a full form is presently 2x to 2.5x quicker than in past discharges. That is a colossal stride forward, however, what designers will probably significantly more acknowledge in this new form is the expansion of another component called “Moment Run.”

This very nearly mirrors the experience of composing HTML, where you compose your code, reload your program and see what changed. On portable, that procedure regularly takes a very bit longer, even with the enhanced form speeds.

Moment Run lets designers assemble and send their applications once (both to the emulator or to a physical gadget) and after that as they change their code and convey it, it’ll just take a second or two preceding they can see those adjustments in the running application.

Source: Google Tech Blog and TechViral

Google has got a revolution in voice thing

Google has built a new technology to power its voice search, which the company says will make it even faster and more accurate. The new technology uses Connectionist Temporal Classification (CTC) and sequence discriminative training techniques. In 2012, Google switched from Gaussian Mixture Model (GMM) to Deep Neural Networks (DNNs), which allowed the company to better assess which sound a user was producing at that time, and delivered an increased speech recognition accuracy.

Our improved acoustic models rely on Recurrent Neural Networks (RNN). RNNs have feedback loops in their topology, allowing them to model temporal dependencies: when the user speaks /u/ in the previous example, their articulatory apparatus is coming from a /j/ sound and from an /m/ sound before. Try saying it out loud - "museum" - it flows very naturally in one breath, and RNNs can capture that. The type of RNN used here is a Long Short-Term Memory (LSTM) RNN which, through memory cells and a sophisticated gating mechanism, memorizes information better than other RNNs. Adopting such models already improved the quality of our recognizer significantly.

The change in technology has been made by Google, and is now being used to power voice searches in the Google app on both iOS and Android, as well as dictation on Android devices.

Source: Google Research Blog