Python the future of digital applications

Is Python the future of digital applications?

It’s no surprise to anyone that computers are getting smarter every second. With more tasks and functions being assigned to digital applications, the era of automation is nigh. Amidst all technological advancements, a lot of it comes from a relatively new programming language that is enabling artificial intelligence to run complex algorithms, so complex that the responses almost mimic humans. A few pointers as to how Python is taking us all into the future.

Future of Full Stack development.

Like many other coding languages, Python has full stack capabilities. This means Python developers can code both frontend and backend for an application across platforms. While this seems like a regular feat, what differentiates it from other languages is the fact that Python can also automate tasks and conduct data analysis amongst many other core functions at the same time. The synergy in functioning of these applications is evidently smoother with intuitive UI and predictive recommendations. All of these features because it has one specific gift which sets Python apart, Artificial Intelligence.

Artificial Intelligence.

Artificial Intelligence. With its learning capabilities, Python accumulates data every step so as to help its systems learn more and achieve further than before. It enables Artificial Intelligence driven applications to gather data sets so as to produce results that are not only accurate but also pre-emptive.

These data sets are generated every time users engage and interact with the applications. Hence, giving the AI-driven technology more information leads it to access and imitate more human-like responses under specific conditions. This interesting bit is what we call Machine Learning.

Machine Learning.

A subset within AI, Machine Learning enables an application to learn from, remember more and continuously optimize user interactions with the interface. This requires constant analytics of data sets and relevant information to provide more intuitive responses that match the user’s subconscious. Moreover, high level optimization of user activities help machine learning systems attain automation. Such applications run smarter and give a far more personalized user experience bringing your business the attention of your prospective clientele. But the scope of this technology doesn’t stop here. It goes much further, much deeper. Let’s discuss Deep Learning.

Deep Learning.

This is where Python gets extremely futuristic with seemingly no limits to its scope. Deep learning enables Python developed applications to train its own algorithms and perform complex tasks that mimic human engagement. This is achieved by exposing vast neural networks to a sea of data. The more information is processed and user actions are predicted accurately, faster the program becomes over time. Deep learning takes automation to a whole different level with multiple split-second responses to extremely complex data imitating a functional human brain. Artificial intelligence attaining sentience might not be too far-fetched a concept after all.

Real world applications.

The advancement in technology and its applications is moving at breath-taking speed. While we use these advancements in our day to day lives, we seldom recognize how smart these automations are. Machine learning has helped humankind in numerous ways already by helping physicians and medical personnel detect disorders as serious as cancer and formulating thorough diagnosis thereafter. Besides these, machine learning also makes facial recognition, handwriting recognition and speech recognition possible which have numerous applications ranging from photo tagging, forensics investigations to converting voice to text real time.

Deep learning feeds neural networks bundles of data and learns from experiences. Hence it’s the core technology that undertakes supervised, semi-supervised and unsupervised learning, runs virtual assistants such as Siri, Alexa, Cortana and such besides managing data and forming patterns for extremely quick decision making that builds the foundation behind driverless cars. Thus Python has reached the level of technological enhancements that’s edging towards an exponentially more advanced digital tomorrow.

Limitations.

Although practically ever-learning as a programming language, Python too has certain obvious limitations, which are still conditional. The continuous flow of the data is the main source for progressive Machine Learning. Hence it’s directly proportional to the data sets available to analyse. If there isn’t enough data, there wouldn’t be scope for further optimization. Moreover, computational training cost too is directly proportional to the number of data sets. Thus it becomes a fairly cost-exhaustive choice for an application. Fault revision remains a major current flaw as well since there are no intermediary steps to resolve the issues. Therefore, Python has its requirements to provide perfection, and rightfully so.

With both applications and customers getting smarter and more used to greater technology, the future is ripe for Python to lead the way. Want your app to be just as smart? Reach out to us and let Skyhawk Kinetic hire best Python developers for your organization. We only deliver the best.