Article

How Deep Learning is Empowering Automated Front-End Development

Topic: SoftwarePublished May 7, 2020
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The world around us is brimming with an endless list of technologies that seek to make our lives easy. We can bank from the convenience of our couch or even buy furniture. Many lives have been made simpler, and contrary to what one may be inclined to believe — technology has made other technology-based tasks accessible as well. Take front-end development; for example — the job of putting together this facet of the website may seem like something that can not be done without human intervention, i.e., programmers coding for hours and hours. Perhaps till a decade or two ago, that may have been a valid and fair assertion, but the advancement of technology now seeks to provide freedom from that task as well. And exactly how can technology take care of this task? We understand it may seem importable, but just take a moment to think of the ocean of advanced, progressive tools we have at our disposal today — big data, artificial intelligence, machine learning, and on and on and on. And amid this abundance of technology that offers excellent potential in the context of front-end development: Deep learning. But precisely what is deep learning, and how can it help? Allow us to explain.

1. What is Deep Learning?

A textbook definition describes it as a subset of machine learning, which, in turn, is a subset of artificial intelligence. But we digress — deep learning is primarily involved with algorithms called artificial neural networks that are underpinned by two key factors about the human brain — function, and state. Simply put, comprised of training and inference, it is a function of artificial intelligence that emulates how the human brain processes data and generates patterns to make decisions.

2. How can Deep Learning Help Front-end Development?

Deep learning, among other things, can help companies and developers automate the process of front-end development. How can that be done? For training in this context, one can provide either screen grabs of the GUI or perhaps even components drawn by hand. The data thus provided for training must also be accompanied by the necessary code for the training data. If you didn’t already know this — one would need a substantial amount of computing power to execute this successfully. Interestingly, there are already prototypes and novice neural networks that have been trained to code websites. It is based on a design dummy. Take pix2code; for example — some folks say that it offers a more than 77 percent rate of accuracy for developing code for web-based tools as well as mobile-based technologies. It is amply clear that the use of deep learning for automating front-end development is still at its very early stages. But the presence of offerings in this market, even though limited in number, are the proof that it can be done. Now, the only thing that remains is for all stakeholders in the world of front end app development to patiently collaborate and drive the change they need.

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