Google Adds AI-powered Capabilities for Android Developers

Google has made it clear in numerous instances that it will become AI-first instead of Mobile-first. This statement makes it pretty clear what Google intends to do with AI capabilities in the future. We are going through an era of technological breakthroughs. Today technologies we are fascinated with, dream of, or saw in movies are becoming a reality. And thanks to Artificial Intelligence (AI), the growth rate is unprecedented. Today everything is becoming smart, owing credits to AI and associated technologies.

Currently, AI is essential to successful development, operations, and every other facet of businesses around the globe. It’s very easy to perform voice-based searches, navigate around an app and communicate with customer service, and many more for AI. Let’s talk about Google’s conference where they released a slew of features and AI capabilities that will help Android Developers. If you are someone who aims to develop AI skills, check out the AI Online Course from a recognized learning partner.

Android Jetpack

Google, in their conference, released Android Jetpack and other programs which will make the developer’s life easier. Android Jetpack is a unified toolkit that will help massively cut the time needed for testing, navigating, or database use-case through a standardized infrastructure. Google summarizes Jetpack to be a set of libraries, tools, and other architectural roadmap to help developers make great apps for Android platform.

Slices and Actions

Coming to the programs, Google introduced Slices which snugs inside the Jetpack toolkit. It will create UI templates for Google Search and Assistant. With this slight addition, Google has opened new avenues or possibilities of creating much more flexible and dynamic functions like voice-activated operations in apps. This feature could well become the future of all Android apps that use AI. Actions on the other hand are also accessories-aware. For instance, if a user plugs in an earphone, it will suggest a few favorite songs that the user might like. Actions will surface in many of Google’s offerings like Google Search, Play Store, Google Assistant, etc.

Google Assistant

Google also introduced Dialog Flow updates, which will help users have conversations with Google Assistant without saying “Hey Google” every time. With this update, users can now generate custom routines and make many requests in one voice command itself.

ML Kit

Google proudly introduced a new Software Development Kit (SDK) named ML Kit in their I/O Developer Conference. This kit helps developers to integrate apps with built-in Google-provided ML models. This ML Kit supports various functions like image labeling, Face detection, landmark detection, smart reply, text recognition, etc. Features like these are available online as well as offline. Developers have to decide on their preferences and network availability. ML Kit supports both iOS and Android platforms.

Google committed itself to developing state-of-the-art features and thus will extend the current base sets of APIs. The best thing about these features is that you can use them in offline modes too. But the trade-off is that you have to adjust with lower accuracy. If you go with the cloud-based approach, you will get accurate results because neither model size nor compute power are issues. So if you go for an offline model, the size of the model will be small, and if you go for a cloud-based model, it will be bigger.

The on-device labelling feature can only help with 400 features for a given photo to identify the subject. That is the reason for its low accuracy, but if you go with the cloud, there will be 10,000 features. ML Kit in Android uses Neural Networks API to power the on-device feature. Google claims that this model is cross-platform and it longer is platform-dependent (iOS or Android-specific).

For Developers

Top management at Google’s division of AI and ML believes that technologically we are at an inflection point, where the way we are developing things is going to change radically. Google through its feedback systems knows that they have to drastically reduce the size of apps and increase user engagement to help make app development faster and easier. If you are a beginner to AI, read through Artificial Intelligence Tutorial to help you get upto speed.

They also released a new app model for Android coming and hinted at coming away from the APK model. This new model is called Android App Bundle. This new format helps in compiling codes and resources useful for an app but differs from generating APK and signing into Google Play. If you are a newbie to APK, let me explain it. APK is a packaging file format for distribution and installation of mobile apps. This file format is used by Android.

So through this new model, Google Play will now use Dynamic Delivery to generate optimized APK’s and serve them suiting each user’s device configurations. The users now only have to download the resource and the code needed to run the app. The mobile app developers no longer need to build, sign or manage multiple APKs that will support different platforms, devices, etc. Instead they will get smaller and more optimized apps.

Conclusion 

Making the apps smaller with much more functionalities was simply impossible with the existing architecture. So to make this happen, Google had to re-invent their architecture and app-serving stack. And they are well on their way to develop the next big thing in mobile app development.