Software and hardware requirements for

Continue Hot on the heels of Developer Preview, Android Studio 3.6 is now available on a stable channel, which means that developers can start making confident use of it for their projects. This brings a number of useful features and updates, including the new Split View's Design Editor for faster design and preview of XML layouts. Another exciting new feature is the support of several displays in the Android emulator. Automatic detection of memory leakage meanwhile promises to make debugging much easier. You can check out the full array of features from the Android Developers blog, or get the highlights below. Split View and EditingPerhaps The most interesting new feature in Android Studio 3.6 is Split View for Design Editors. This allows you to see the XML code side by side along with the preview render. It's a small thing, but in fact it makes life a lot easier to view the effect that changes the code right away (and vice versa). The view you choose will also be saved on a case-by-case basis, which means you can easily download the preferred setup depending on the file you're editing. While we discuss design, we should also note the new color collector, making it much easier to select and fill color values without a set of values. It's available through the XML editor and design tools. Faster development When it comes to development, a few new changes should make life easier for Android Developers in Android Studio 3.6.View Binding is a particularly welcome inclusion that will offer a compilation of security time when linking to opinions. With this option, you'll create a binding class for each XML layout file in the module. This will actually replace the need for findViewByID: you can easily refer to any type of ID without risking zero pointer exceptions or class exceptions. This can prove very useful and reduce a lot of patterns. Other new updates include the release of the IntelliJ 2019.2 platform with better launch time and new tool services, as well as support for Kotlin for more Android NDK features. Updates to the Android Gradle plug-in include support for the Maven Publish Gradle plug-in. This allows you to create artifacts in the Apache Maven repository. Testing and debugging Android Emulator 29.2.12 makes it easier for developers to interact with the location of the emulation device. Maps is now built into the advanced control menu, making it easy to specify locations and create routes. Perhaps more appropriate is still the support of several virtual displays that will be useful for those designing for devices such as Samsung Galaxy Fold.Read also: Development for folding devices: What you need to know, memory detection detect activity and snippet instances that may have leaked. Build time has also improved for debugging builds thanks to the use of quality of life changesIt's only a small selection of updates available in Android Studio 3.6. You'll find plenty of other small updates as you use the new software too: including the resumed SDK downloads, which is perfect for those who don't always have an hour spare to download the latest Android image! Grab Android Studio 3.6 here. Of course, on the Canary Channel you can already get your hands on Android Studio 4.1. What do you think of these new features? What would you like to see come to Android Studio in the future? What is the future according to Google? It's a pretty exciting place. Artificial intelligence rules supreme. All the information in the world is available right at our fingertips, and of course Google is the company to provide it. is at the heart of everything that Google doesGoogle may seem diversified in recent years, exploring everything from self-driving cars to smartphones. The truth is that machine learning is actually at the heart of everything it does. Google started out as a , and has naturally expanded into machine learning and AI. In this way, Google can understand the questions you ask it and provide the appropriate answers, rather than just a list of search results with appropriate phrases. Search engine optimizers will be familiar with the algorithm 'RankBrain' that feeds this smart search. evolved from the same natural language processing, combined with voice recognition, which made it possible through machine learning. Similarly, initiatives such as show us how machine learning can be used using computer vision to help us find what we face in the real world. In fact, AI-first is not a step away from search, but its natural development. But it goes much further. Why does Google need hardware for its vision to work, does something like Google fit into it all? The answer is simple: in order to make the most of artificial intelligence, which is ultimately a form of software, Google needs the right hardware to run it. Google wants to become a go-to solution for AI, just like it's a go-to search solution. This means that he wants to put a Google assistant in his pocket. Google Assistant faces competition from Apple, Microsoft, Amazon and even Samsung. Seeing as AI is likely to dominate the industry in the coming years, Google will have to fight to get ahead of this package. If you have a Google assistant in your pocket, why would you ask an echo point to set a timer or save a reminder? As our own Bogdan Petrovan suggested in his recent article, Google may not really care smartphones it sells. The key is to demonstrate to other OEM manufacturers how close integration with its services can help them satisfy customers and put pressure on companies to place the function front and center. Because the pixel and and The two exist as viable alternatives for consumers, OEMs must ensure their devices also offer Google Assistant to stay competitive. Google wants an assistant front and center on every smartphone, even iPhones! This means that it should have some impact on the direction of both hardware and software. This symbiotic connection works both ways. The hardware supports Google's vision of conquering AI, but AI also creates new hardware capabilities that might not exist otherwise. Google CEO said he doesn't just want Google hardware to use AI in the future, but wants AI to inspire future products that might not exist otherwise: is a great example of this. Even Google's self- driving cars are an example of machine learning apps, relying on how they are on computer vision in order to identify hazards and respond accordingly. The role of cloudIt has become clear that Google has a very clear plan for the future and it revolves around machine learning and AI. The goal is the same as ever: Organize world information and make it universally accessible and useful. It has become apparent that AI and machine learning offer the best tools to achieve this. The equipment serves as a channel between user and machine learning, and encourages other OEMs to get on board, showing what is possible. To be clear, AI and machine learning are not the same: machine learning is just one aspect of AI that handles image recognition. As always, Gary explains the differences best. Virtual assistants such as Alexa, Siri and Google Assistant are currently working on the cloud. Your voice commands are saved, processed to some extent, and sent to the server for additional processing, so that the answer can be generated. This is necessary because most smartphones do not have the necessary power for the intensive algorithms on which machine learning relies, such as image recognition, necessary to understand voice commands or to recognize distinctive patterns in images. Instead, hard work is done on the cloud. To do this, Google uses an initiative called TensorFlow, a library of useful machine learning algorithms processed by the Cloud Tensor Processing Units (CTPUs) that work on their servers. The exciting part is that developers are free to use these offers through Google's cloud platform. Is there an idea that requires machine learning to work? Now you can make it a reality! This is another example of how Google is delving into the hardware to way into AI, but it also shows why the cloud is such a necessary part of his vision. The problem is that AI applications are somewhat limited by being unloaded this way. This not only creates an obvious speed bottleneck, but also introduces new security problems and requires a permanent Internet connection. If you have an idea of an idea requires machine learning to work - and now you can make it a reality! Fortunately, we are on the verge of the hardware that ai can offer on board thanks to new neural processing units (NPCs). Google includes - the company's first mobile chip, which unsurprisingly engages in machine learning. The chip is designed to help support hdr' function of the Pixel camera, which in itself is a function of machine learning. This is an advantage provided by Google by taking control of its hardware. In the future we might see this leading to more image and machine learning applications too. Other companies are also coming out with their own NPCs to better handle AI applications on the device. Phones do not need strictly these types of specialized chips to handle machine learning. Your GPU can do the same much more slowly, and even has a built-in TensorFlow Lite to act as a built-in, easy-to-use solution for mobile devices. But specialized hardware can help you make services much faster and more powerful, while introducing brand new applications and benefits, especially in areas such as security. Google's vision for the futureSlet overstate that introductory question: what does the future look like for Google? We can still only guess, but based on everything we know, we can safely say that Google hopes that you will use Google Assistant to handle a number of tasks. If you want to set a reminder, find out where to buy a product by pointing to it, or hear a joke, you ask your phone. Similarly, if you want to find a recipe, send a text, or check how long it will take to drive to work, you will choose Google Assistant. It could soon be processed on board your smartphone - whether it's a Pixel, a Galaxy, or an iPhone. To this end, we can assume that Google will experiment with Pixel Visual Core, bringing new AI features to Android and potentially anticipating its next wave of hardware with a more powerful NPUs.Your phone will know you closely and this will allow it to pre-empt your requests. It will send you reminders, keep your data safe and of course provide you with personalized purchase recommendations. But the same technology is likely to power a host of other tools and gadgets: from augmented reality offerings like , to self-driving cars and smarter cameras. Third-party developers will use this technology in a variety of ways we can't even think about yet that could change our lives. Maybe we'll have refrigerators that order our food for us because they know what we'd like to eat, or maybe we can dictate and the word processor improve our writing style as we do. But whenever we use an app like this, it will be powered by Google and Google will get a cut. Everything Google has done he first started indexing the internet to search for it for this future - even if the company didn't understand it at the time. Will Google succeed? So, will Google become the actual virtual assistant in a world where AI rules supremely? Thanks to all the work that Google has done with search, this is perhaps the strongest position to become the ubiquitous AI of choice. Through search, Google relies on publishers to make their content more AI friendly. Initiatives such as structured data markups help bots pull key parts from a piece of content, such as ingredients needed for a recipe or date and concert time. This allows Google to actually answer questions rather than just direct users to the web page. This is an additional code added to websites by developers to identify important details. Google made it happen by using its position as the number one search provider. Publishers had to play ball if they wanted to keep their sites at the top of the search engine results page (PLEASE). As a result, and Google assistant get smarter. Of course, everyone can choose to use rich snippets this way, but no other company has a huge link index to make full use of this feature, nor leverage with publishers to make such a fundamental change in the way that information is shared. Thanks to Android, Google has a huge impact in the hardware space too. Google is positioned as a formidable player to say the least, and it has significant resources and the necessary focus to make sure it eventually wins. Google is positioned as a formidable player to say the least, and it has significant resources and the necessary focus to make sure it eventually wins. This Google.ai focused on research as well as the development of tools such as TensorFlow, Cloud TPUs and Applied AI. Numerous strategic acquisitions only strengthen its position and increase those resources. But there are pockets of resistance. Shots have been fired and it seems that companies such as Apple, Huawei and Samsung will not go down without a fight. By creating a special button for Bixby, Samsung takes a clear position in trying to take responsibility for its own AI offerings. Similarly, the A11 chip in the new iPhone and Kirin 970's Mate 10 are neural processing units designed specifically for processing on-board AI, which may be relative to Google. Microsoft's Cortana has the advantage of Bing and the rigid integration of Windows. Amazon may not have the same search power, but it may offer some smart trading features that won't be possible elsewhere. In short, we may well see a battle for AI supremacy in the years to come. Smart on Google, but who knows what's to come. 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