Blog: Software Development: Time to Revolutionize using Machine Learning
Technologies like artificial intelligence, machine learning are a misnomer. I personally feel that a machine can never learn or there is no such thing as the intelligence of a machine. And no matter how advancements we come up with; no device can ever be imbued with the intelligence of a human being. However, if we look at the positive side- machine learning when incorporated by development companies can offer intimidating results like never before. There is no denying in the fact that they present a new paradigm for upcoming services in the industry. Let’s find out more about it!
Machine learning is poised to change the fundamentals of software development anytime soon. In fact, since its inception, these technologies have proved the way they end up reducing the most time-consuming, manual tasks that keep sales teams away from spending more time with customers. Automating account-based marketing support with predictive analytics and supporting account-centered research, forecasting, reporting, and recommending which customers to upsell first are all techniques freeing sales teams from manually intensive tasks.
Difference between ML and AI
Those machines which fully replicate and even sometimes surpass all human’s cognitive functions — yes the ones which were dreamed about in science fiction stories have become today’s reality. In simple words, ML mimics how the human cognitive system functions and solves problems based on that functioning. It may quite interest you to know that it can analyze data that is beyond human capabilities. ML, when used in the software development cycle, can make UX immersive and efficient while also being able to respond with human-like emotions. Several professionals feel this tech as a threat as they have the potential to beat us like a game of chess. Right from recognizing images more accurately to transcribing spoken words more precisely, these techs can do anything even translate over a hundred languages in no time.
Real- Life Applications
- Amazon Echo, Google Home:
- Digital assistants: Apple’s Siri, SAP’s upcoming Copilot
These devices provide an interactive experience for the end users- all thanks to Natural Language Processing technology. Keeping ML in the picture, this experience might be taken to new heights, i.e., chat-bots. At the Initial stage, they will be a part of the apps mentioned above, but it is predicted that they could make text and GUI interfaces obsolete!
However, these technologies does not force the user to learn how it can be operated but adapt itself to the user. It will become much more than give birth to a new interface; it will lead to the formation of enterprise AI. Fortunately, there are limitless ways in which ML can be applied such as the provision of completely customized healthcare. Time will come when these technologies will be able to anticipate the customer’s needs due to their shopping history. It can make it possible for HR to recruit the right candidate for each job without bias and automate payments in the finance sector.
Areas Where Tech can play a Pivotal Role
- Bug Fixing- One of the crucial areas that need to be revolutionized with AI and Machine Learning technology. Day by day, companies are facing huge volumes of data that needs to be tested, and human error due to overlooked bugs, software testing tools such as bugspots show us that programs can leverage AI algorithms to auto-correct themselves with minimum intervention of a human programmer.
- Code Optimization- Gone are the days when fixing code without the need of original source was hard to achieve. Today, with the help of compliers processing high- level programming language and converting it into machine language or instructions is easy like never before.
- Testing- AI-driven testing is not new anymore; it has been in talks over a few years. Fortunately, some open source tools uses AI for generating test cases and perform regression testing. Appvance, pegged as an AI-driven software test automation tool uses AI for performance and load testing and to generate test cases based on user behavior.
Apart from these, machine learning provides rapid prototyping, intelligent programming assistants, automatic analytics and error handling, automatic code refactoring, precise estimates, strategic decision-making and what not! Also, the future of consumerism and business optimization relies on the artificial intelligence of machine learning.