A wave of warning – the dystopian future scenario of a killer robot is closer than we imagine.
Artificial intelligence is now the key to world domination as believed by Russian President Vladimir Putin. AI is poised as the most promising development for the nearing future. From helping cure cancer and resolving the hunger crisis, artificial intelligence is a solution to all our problems. However, to others, it is regarded as a threat giving rise to unemployment. But as Elon Musk puts out stating, “The benign scenario is that artificial intelligence can do any job that humans do – but better.”
AI is getting ready to transform software development, but is software development ready for AI?
In the past 25 years, AI technology has grown by leaps and bounds. Thanks to the emergence of data and cloud computing, the pace at which AI expands today is incredible. Software development is now seen at the core of all innovations. From Google Photos to Amazon’s Alexa, and autonomous cars developed by Tesla, it is already living with us.
The shift toward how data – the heart of developing a software system causes big giant companies to not only rethink how to develop software but the kind of tools that are required to transform this paradigm shift.
AI and machine learning in software development. What’s the connection?
AI-powered tools have proven to increase efficiency in software development. Developers and programmers are now adopting these tools to help identify and fix bugs in their programs. These tools not only provide developers with cloud-based IDEs but also help in carrying out deployment control.
From this standpoint, one possibility is certain – is that software developers will require to put in more effort into data collection and preparation. Machine learning is nothing if there’s no data to be trained. Thus said, programmers will not only need to collect data but build data pipelines and infrastructure to manage these pipelines – “data engineering.” In such cases, these pipelines will make use of machine learning for monitoring themselves.
It is difficult to imagine a world where humans will no longer need to create software. But imagining “human in the loop” software development will still be a bigger part of the future.
The time may have finally arrived for AI professionals to harness their powers.
How AI and ML are transforming software development?
For decades now computer scientists have been making efforts of using AI programming techniques to transfer business policies, decision-making, and human-level knowledge to computers. Though it seemed fancier than just programming, AI-based techniques were used to enhance the system’s knowledge base, a system that always had limitations.
“A computer would deserve to be called intelligent if it could deceive a human into believing that it was human,” says Alan Turing.
Having said that, limited domain knowledge proved to be futile for human expertise.
But the new AI approach is building systems that are capable of learning by themselves.
Here’s how the expanding basket of AI tools and technologies will change software development for the betterment.
Be a bug spotter and patch bugs
Thanks to the emergence of AI-powered tools, developers can now easily identify bugs, code better, and fix these bugs. Besides becoming great bug fixers, developers also get the opportunity of using machine learning algorithms while testing software programs. With the advancement in AI, testers along with developers look forward to using AI-powered tools in helping them find software flaws and fixing them automatically.
Nurture young talent in software development
Young talents are considered an integral part of the development community. AI provides them the opportunity of gaining expert insights on developing a new software program. With the help of AI-powered tools, developers can now collaborate on software programs as well.
As the world embraces AI revolution becoming an AI engineer is perhaps a great career choice for young talent in the software development field.
Often developers come across challenges such as code duplication and omission of certain parts of code. To prevail such hazards from taking place, developers can make use of coding tools powered by machine learning algorithms to make their coding intelligent. Such tools can help identify the silliest error while coding. Apart from this, these tools help developers with a code editor that format parts of the code based on the programming or language used.
An entry to cloud-based integrated development environments
An integrated development environment (IDE) is where programmers find a place to edit, debug or compile their code. With the help of cloud-based IDE, a developer can easily write and store the code on the internet. Safety and convenience can be attained through IDE, a platform where developers do not need to fear to lose their work once laptops or desktops crash.
AI-based technologies not only increase the efficiency in deployment control activities but also necessitates the development phase where developers are required to upgrade applications to newer versions. Failed execution incurs huge losses to the development process ruining the software program and application.
However, with AI technologies developers and programmers can now easily run newer versions of software applications without worrying about failed deployment. Problems related to the deployment process can now be detected using machine learning algorithms.
The future beyond software development
Despite agreement that AI is making huge advancements in software development, the question remains the same, “will artificial intelligence be able to subvert the human need for technology development?”
Undoubtedly, the current AIs impact on software development is still at its initial stage. Software development companies will continue building machine learning AI dominating every facet of design and creation of the software.