Why Machine Learning And Progressive Web Apps Are A Great Match
Machine learning and progressive web apps (PWAs) have a lot of benefits to offer each other, and they work fantastically together. Here's why and how.
Machine learning is playing an increasingly important role in web development. Responsive web design practices first started becoming popular around seven years ago. However, advances in machine learning have made them much more robust. One of the most important ways that machine learning is changing the Internet user experience is with the development of progressive web applications (PWAs).
Info World published an article about the importance of PWAs last year. The authors pointed out that PWAs solve many of the key problems with traditional online apps. They are still a relatively new concept, but PWAs have already proven their versatility and started improving the user experience.
Machine learning technology is going to be vital to the future of PWAs. It will make it easier for PWA development teams to ensure every user has the highest quality experience.
What are the core benefits of PWAs?
Progressive web applications are hybrid platforms that combine the best features of traditional websites and online apps. There are a number of reasons that they are setting new standards for user engagement.
PWAs load much faster
Traditional apps are not known for their fast loading times. PWAs are raising the bar with speed. One study found that they load 15 times faster.
PWAs don’t need to be installed like traditional apps
One of the biggest downsides of traditional apps is that users need to download them to their mobile device. This is highly inconvenient for mobile users. They take up a lot of memory and leave the mobile desktop looking very cluttered. Some apps also have glitches that interfere with other features, which encourages users to uninstall them.
Due to these problems, 28% of all apps are uninstalled within 30 days. This is obviously a huge problem for businesses that are trying to expand the reach with mobile apps.
PWAs, on the other hand, do not need to be installed. This is possibly the most important feature of them.
PWAs can be accessed off-line
Traditional apps obviously require an Internet connection. Although many features require a network connection for obvious reasons, there are plenty of simple features that should not require one. Unfortunately, people using conventional apps are not even able to use these features.
PWA developers recognize this inane limitation. They have created apps that can be accessed off-line. These apps use sophisticated data technology and machine learning algorithms to get a better pulse on their users. As a result, they can deliver an exceptional user experience for many features that don’t require a connection.
PWAs can interact with other devices to deliver superior functionality
Traditional apps are able to connect with certain devices on the Internet of Things. However, most devices are not compatible with their programming interface.
PWAs are different. They can connect to motion sensors, virtual reality technology and much more. They can also handle push notifications and other web features that are not available with most other apps.
Machine learning is making significant headway here. Machine learning algorithms are used to improve both the performance of apps and the technology that will connect to them. Once compatibility constraints between the mobile device and third-party technology are sorted out, the technology can be easily merged. As a result, PWAs allow for how much more holistic experience.
Security concerns have dissuaded many people from using traditional apps. It can be difficult to resolve all known security flaws in an app after it has undergone beta testing. Many security features are not even discovered during the initial testing phase. Users might not discover them until after their device has been hacked.
PWAs have helped improve app security significantly. Due to the configuration and network requirements, all traffic must pass through and HTTPS connection. The high level of encryption means that security risks are going to be very minimal.
Machine learning is also helping improve the security of PWAs. Big data algorithms are constantly screening all web packet connection requests to identify suspicious Signals. As they become more familiar with hacking attempts, they will be able to update their algorithms to provide stronger security.
Machine Learning Leads to New Advances in PWAs
Progressive web apps are setting a new standard for the mobile user experience. They rely heavily on machine learning, which is helping make them faster, safer and more convenient. What is the future of machine learning and PWAs? Only time will tell.
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