AI-powered tools have been increasingly used in software development with the booming advancements in the artificial intelligence field over recent years. This shouldn’t come as a surprise. Machine learning technology has gone a long way in becoming the go-to computer algorithm it is now. With companies leaning towards incorporating the best artificial intelligence software into their internal processes, the competition among market leaders becomes as tough as ever.
If you want to stay relevant and profitable, you might learn how to use AI software development tools in your future projects.
Maybe the chances of you becoming the next Elon Musk with his AI-powered Tesla or Jeff Bezos with his groundbreaking Amazon Echo are low. However, the applications of AI-powered tools in software development can be game-changing for your business too.
Keep on reading to find out the latest innovations in artificial intelligence 2021 and how you can leverage these AI software tools to stay ahead of the curve.
What is Artificial Intelligence?
Artificial Intelligence (AI) is a modern-day technology that allows machines to learn from experience, adapt to new inputs, and execute human-like tasks without relying on humans. Self-driving cars and chess-playing computers are just some of the examples of AI. They are heavily based on deep learning and natural language processing.
By using these technologies, computers can accomplish complex tasks as they process big data, recognize patterns in this data, and make the most of it. This is how companies that are known for dabbling into AI have a competitive edge over their competitors.
What is the purpose of AI in software development?
Current AI investments across the globe account for 80% of usage by companies in all industries. This number will keep growing as more players on the market will discover the advantages of implementing AI development tools in their operations.
How come? Below are the main functionalities you’ll find to apply to software development in particular.
As you can tell, AI software development tools assist the democratization of coding, which eliminates the need for manual labor and increases the efficiency of tasks. This takes off the unnecessary pressure from software engineers who might not excel at coding. It also helps automate code writing, bug fixing, and software development projects organization for a more streamlined workflow.
Besides, software development backed by AI enables companies to offer exceedingly customized products and services that stand out in the crowd.
How AI and machine learning transform software development
AI and machine learning are the things that are changing the way software is developed completely. They not only add the element of automation that permits software engineers to focus on the bigger-picture tasks. They make it possible for innovation processes to develop at a much quicker pace. This is excellent news — the more advancements AI and machine learning facilitate, the more efficient our lives become.
“Once it masters the underlying patterns, besides code completion, an AI system could generate a program by putting together some predefined modules, just as LEGO pieces.” – is sharing his excitement a user of Reddit. Optimum Web developers understand him perfectly.
Take a look at some of the most common transformations already happening in software development thanks to the evolution in Artificial Intelligence:
Deployment operations are a lot easier to manage
Since continuous upgrades are ordinary for code-based applications and programs, the consensus is that they take place with as few errors as possible. Having AI and machine learning in place, the risk of failed deployment falls significantly. As a result, software developers can freely run the latest versions of these applications. They rely on tested machine algorithms that don’t malfunction nearly as often as the regular ones.
Mistakes occurring during coding are at an all-time low
It seems like a no-brainer, but with automation comes reliance on the systems designed to take human error out of the equation. When writing code, it’s not uncommon to make mistakes. This is why when AI and machine learning are integrated, duplications and omissions associated with code are easier to avoid. Add the code editor to the mix, and you’ve got a mistake-proof formula for writing flawless code every single time.
Spotting and fixing bugs doesn’t come with difficulties
Perhaps the biggest inconvenience in software development is coming across bugs that can ruin the smooth running of the program. They need immediate fixing, and this is where Artificial Intelligence comes to the rescue. Besides, software developers can also reap the benefits of using machine learning when testing software as it allows them to pinpoint the faulty code much faster.
The 4 latest advancements of AI in software development
Artificial intelligence tools and techniques have taken a different form in software development, and everyone’s here for it. We’re talking about the appearance of efficiency-inducing instruments that make it easy to come up with more intricate programs and applications aiding every industry under the sun.
One of these novelties is GitHub Copilot, the AI programmer that takes the guesswork out of coding and provides you with hints for writing better code. You don’t even need to be proficient at programming. The tool can adapt to your code writing style so that you end up with a perfectly well-functioning code.
Employed by thousands of Python developers worldwide, the free AI software Kite remains one of the most sought-after programming tools compatible with 13 languages and 16 editors/IDEs. It works as a plugin based on a deep learning algorithm allowing you to achieve the highest possible code completion confidence.
This code autocompleter tool’s suggesting qualities make coding a walk in the park by aiding in writing complex codes. Built upon GPT-2, TabNine is unlike other code completion plugins. It uses the programmer’s past code usage history to make accurate predictions in the completion candidate box.
Clever-Commit was developed for bug prevention and resolution purposes (which is literally what the acronym stands for) that’s currently being used solely in gaming. It’s a game-changer in the IT industry due to its nature that combines data coming from the bug-tracking system and the base of codes used to search for errors in the code.
Benefits and risks of using Artificial Intelligence tools in software development
Artificial Intelligence in software development, inspiring and innovative as it is, has its benefits and risks like any other technology. Before you decide to employ the best artificial intelligence software there is, you should evaluate its pros and cons so that the benefits of integrating it outweigh the risks by a significant margin.
Why research AI safety. Key risks of using AI-powered tools in software development.
It might be tempting to adopt the latest AI and machine learning tools without prior research, but this can backfire. To avoid having to fix the issues that come with implementing technologies that aren’t widely adopted just yet, consider assessing the following AI-related risks:
The bias of algorithms
Similar to confirmation bias in human psychology, automation bias is an integral part of Artificial Intelligence that makes humans favor automated decision-making over the one made by humans. This can lead to the spread of false and discriminatory data. It will cancel out the efficiency of the machine learning-based software it was intended to offer in the first place.
It’s hard to come to terms with the fact that we create as many as 2.5 quintillion bytes of data every day. This staggering figure is further supported by the need for AI systems to rely on vast amounts of data to function properly. The result — privacy has to take a back seat for automation to work without fault.
The emergence of hacking algorithms
Speaking about privacy, the logical conclusion would be that open access to data and code makes it easy to hack AI algorithms and cause businesses to go bankrupt or, worse, become subject to lawsuits.
Even if possible to be mitigated, these and other risks still pose a real threat to the further advancement of AI-powered tools in software development. For this reason, programmers are still using this tool with caution for informational purposes, and the rights/license to use code snippets remains an open question.
3 Benefits of using AI-powered tools and machine learning in software development
There’s a bright side to AI software and machine learning too. Suppose you take the privacy of your data seriously and stay flexible instead of the constantly updating and evolving AI-powered technologies. In that case, there’s a good chance that you’ll beat your competition without having to reinvent the wheel. Here are some of the benefits of adopting AI-powered tools in software development:
More high-quality software that doesn’t crash easily
Bugs and errors are synonymous with software, and if there’s a way to minimize both, it’d be not very smart not to use it. Artificial Intelligence and machine learning have the unique characteristic of learning from the past, which puts them at an advantage by default. And when there’s a system in place to foster more efficient and faultless coding, software developers are more eager to experiment and innovate.
Quick and efficient identification of bugs and errors
When you’re integrating AI tools, writing code becomes easier. There’s no need for coders to search for bugs and errors manually. The deep learning algorithms do this for them.
Improved accuracy of estimates
Due to AI being able to analyze historical data from previous projects and find correlations with the present ones, there’s a greater likelihood of it better estimating the software. This translates to fewer miscalculations and more efficiently-working programs and applications.
P.S. Some Optimum Web developers are using Kite plugins in PyCharm and Intellij IDEA working on services the company provides. “Although the AI-based development tools are still imperfect, they completely changed the way I write code. It’s building so many things I’ve always wanted.” – shares one of our colleagues. “We are looking forward to expanding the range of AI-powered software development tools we use.”- is his team leader’s conclusion.
There’s no doubt that Artificial Intelligence and machine learning are changing how software development approaches these days. Software developers that are new to the game feel more empowered to dip their toes into more experimental coding. Thus they find new and more efficient methods of writing code. At the same time, seasoned professionals can be confident in stepping out of their comfort zone and taking on more responsibility when deploying programs of varying difficulty levels.
This points that while Artificial Intelligence can be a handy tool for software developers, we still need to check whether it is ready to help programmers at this stage of development. Evaluate the risks, test out currently available Artificial Intelligence tools and techniques, and adopt the ones that seem to carry the least amount of repercussions for your company.