Android is another platform that Google has focused on and its efforts are clearly visible: Android occupies more than 87.9% of the market share. With the latest Android P right around the corner, it seems like a great time to take the best of both worlds: Machine Learning and Android and show why Android is more likely to beat its competitors using Google’s mammoth intelligence prowess. and why AI will. appeal to everyday users as well as developers.
Here are some reasons why.
Google announced its virtual assistant in May 2016 during its annual conference, Google I/O. Google described it as a “conversational assistant” and hoped it would provide “an ambient experience that spans across devices.” And the feedback received has been mostly positive.
Of course, Google isn’t the only one trying to help its users with software. In fact, it’s not even the first: Apple launched a beta version of Siri with its iPhone 4S almost a decade ago, in October 2011. To say that software like Siri has come a long way in these 7 years would be outrageous. attenuation. It seems like all the tech giants release their own assistants every other week. While the standouts are Microsoft’s Cortana, Amazon’s Alexa, Samsung’s Bixby, Google Assistant, and Apple’s Siri, almost every review from professional testers reveals the one that manages to spin just about anything thrown at it. And that’s the Google Assistant.
It has proven its worth countless times in tasks ranging from speech recognition and contextual understanding to providing concise yet detailed information to any user query.
Some would say it’s years ahead of other virtual assistants, though advancements like Duplex only confirm that.
Tech giants are recognizing the importance of incorporating machine learning into their products, and as our systems become more powerful and people generate more data than ever before, it’s no wonder why they do so. This is evident in companies that embrace and promote intelligent computing.
Apple has been urging developers to use its relatively new CoreML framework that can be used to train machine learning models to develop apps for iOS. It’s too early to pass judgment on this step by Apple, but it’s pretty safe to say that the red-berry iPhone maker is late to the party.
Google released an open source framework called Tensorflow in 2015 after it was tested and developed internally for over 4 years. Since then, it has earned the industry standard badge and is one of the most active repositories on GitHub. It was developed with developers in mind and has multiple ports for different operating systems and also supports multiple programming languages to make a developer feel at home.
Tensorflow Lite is Google’s goal to have native support for its deep learning models on Android phones. Apps like Gmail are already putting this to use by introducing something called “Smart Replies” which basically just tries to understand the situation and context in a received email and will display some options that might be a good response to the above. Another famous app is Google Photos which uses deep learning, a popular form of machine learning, to recognize people from images stored on the smartphone and suggest possible options such as sharing them with the person or creating a whole new album. for them.
To make a long story short, Google has already started releasing apps like Translate, Assistant, Photos, Gmail, etc. and has created the necessary tools for developers to do the same with theirs. Which brings us to the next topic:
Excellent support for developers
Google has always been a beloved by developers. In addition to offering great opportunities as GSOC, it has released open source libraries such as scikit-learn and TensorFlow that have been very popular and successful within the developer community.
Even Android, being open source, offers a lot of flexibility for developers, and therefore, naturally, developers will be much more focused on creating applications that are scalable and optimized for this platform.
Google wants more and more people to get into this machine arena and has worked hard to do so. One such case is their Machine Learning Crash Course. It is a ground-up course aimed at developers with almost no previous experience in the field of AI. Guides the user from the basics of linear algebra to state-of-the-art convolutional neural networks.
Android developers drew attention with the announcement of Tensorflow Lite, which is an ecosystem for the Android platform. It works seamlessly with the official Android IDE, Android Studio to develop apps with the same level of consistency as before.
Google did not fail to wow the visitors and viewers of its 2018 developer conference with pure amazement. He showed off something that the developers at Google had been working hard on, called Google Duplex.
It’s an extension of the already powerful Google Assistant that helps the user get through the day by making appointments or booking services like ordering food from a store that doesn’t have an online presence or getting a haircut at a salon to use.
It was introduced by Sundar Pichai, leaving the audience in applause. And why wouldn’t they? They witnessed an age-old test called the Turing Test that was supposed to be almost a decade away from being solved, albeit killed in a very specific way.