“Robots are not going to replace humans; they are going to make their jobs much more humane. Difficult, demeaning, demanding, dangerous, dull – these are the jobs robots will be taking.” – Sabine Hauert
If you still think of Artificial Intelligence (AI) as this highly complex invention that is far from being widespread in almost all our everyday areas, think again. AI is already all around us – from self-driving Tesla cars minimizing risks of human errors, to apps for real time traffic navigation (e.g. Waze), to AI powered search engines, to enhanced medical image diagnostics and even AI music composition. Yes, the development process will not be left behind from AI related innovations.
From my experience working in a bespoke software development company, AI and its subset, machine learning (ML), are exciting areas for developers who want to benefit from the powerful capabilities AI-based tools hold. We now observe how AI is getting much more complex each year and how it has slowly, but surely, become a big part of our daily lives. At the moment, the software development process has had many touchpoints with AI and one can begin to imagine what a programmer’s job would look like in the future. Let’s see what the lies in store for developers.
How is AI Used in Software Development?
Artificial Intelligence has a lot to offer with regards to improving software development processes. It is already being partially used as a standard in some important areas. As the AI grows and expands in knowledge and capabilities, the horizon of a software developer broadens as well. What may have seemed futuristic becomes the new normal. For example, AI software and tools assist dev teams in automated debugging. Deep learning can flag-off errors and accelerate the processes and even automatically correct mistakes in the code structure.
Furthermore, AI is widely used for the development of smart software assistants that help junior programmers avoid common beginner’s mistakes. Such assistants for Python are Kite, Sourcery, Flowbot or TabNine. AI is also believed to prove useful in software testing where AI-based automated testing could take over repetitive and monotonous tasks. This allows QA specialists to focus on more complex issues. With automation of test case writing, AI testing tools will be able to help testers detect code that is not yet covered within current test suits and cover the source code’s control path.
Automotive code generation is another software development area that can benefit from AI-driven solutions. AI can significantly reduce the sometimes tedious and time-consuming task of writing code from scratch. Similar to solving a puzzle, AI can assemble the pieces together to create a program from predefined modules. When an AI powered tool steps in and after it has made sense of and mastered the necessary patterns from the provided input, AI would be able to generate software products. Technology is always changing and evolving; what is the standard now may soon be outdated, It is exciting to know that the biggest potential of AI features has yet to come.
AI in Integrated Development Environments (IDEs)
Integrated Development Environments, or IDEs, offer various functionalities like code completion, syntax highlighting, debugging, variables editors and package management. With an IDE, developers spare themselves huge amounts of time when it comes to configuring different tools and switching from one to another. Moreover, IDEs boost productivity because it is easier to analyse the code, to check the syntax for errors and to get instant feedback when such errors occur. So, how can this software application be enhanced by AI?
Well, AI and ML can drastically change the game when it comes to intelligent full-line code completion, like IntelliJ. An IDE for Java that can also assist languages like SQL, JavaScript, JPQL, HTML or Codota, which supports almost every programming language. Serious advancements have already taken place with the use of ML to smoothen the development process and provide in-depth framework-specific assistance.
AI is also used to assign attributes to different code completion alternatives. AI can then rank them according to their relevance so that the most relevant attributes are shown on top. This way, developers avoid time-consuming searches for code examples and can ensure the suggested codes are relevant to the IDE context. AI can also support and improve collaborative editing processes and expand the use of IDE as a lightweight text-editor. Thus, making the development process a lot easier and more interactive.
Generative Pre-Training Transformer 3 (GPT-3)
This is probably the next big thing in AI and the fuss surrounding it is well-deserved. To get an idea of what the GPT-3 is, imagine an AI that is the best in content creation, based on either human or machine language. GPT-3 is essentially an autoregressive language model with 175 billion parameters, using deep learning to produce written language (text) and code in CSS, JSX, Python etc. It was developed by OpenAI, a company co-founded by Elon Musk, and was initially introduced in May 2020 as a research project. In July, a select group of specialists got the opportunity to test the current beta version. If you’d like to gain access, you must enroll in the waiting list.
As astonishing this sounds though, OpenAI CEO Sam Altman reminds us that it still comes with drawbacks. For instance, the model uses enormous amounts of computing power, which can make it unaffordable for smaller companies. Secondly, there is a certain mystery around how exactly software products are produced, as the algorithms are “sealed” in a black-box system. Lastly, GPT- 3’s capacity to create complex applications at the moment is pretty basic and will need technical improvements over time.
Ultimately, developers may be threatened by GPT-3 if it reaches a commercial level. This is because a non-tech person could potentially code a simple software within minutes. This tool carries great potential to revolutionize the development process by simplifying the process of developing a software simply by stating it in understandable language. Software developers may use it to complement their current dev process by delegating the hard work to the model and refine the code by themselves afterwards. It all depends on how one views it: as a danger or an opportunity.
In a nutshell, AI is expected to change software development by making it easier to design, develop and deploy quality software at a much quicker speed. AI-powered tools will increase, both in quality and quantity, with the tendency to become more accessible and affordable, even for smaller companies. In the future, AI solutions will be more reliable and would empower software developers to create even more innovative and competitive products. The question that still remains is: How are you going to be a part of that future?
