Role Of Artificial Intelligence In Mobile Apps

25 Feb

Remember how Hollywood used to show that “Artificial intelligence is coming for us all” or “There will be a time Humanoids with self-driving cars will take over our world” and painted all the “end of days” dystopias through their films back in the 1990s?

Well — they were wrong.
AI is nothing like that today!

In fact, it is a decent indicator of how far we all have come, and how far we can predict our way forward.

What previously was only a technological dream (and a nightmare for some) presented in sci-fi movies is an integral part of almost every tech space today.

Everything from virtual assistants to chatbots to advertising and self-driving cars — AI, along with its allied disciplines like machine learning (ML), has completely revolutionized the world.

And the promising results of all the advancements we've made in the field of customized application development by the likes of AI are also, indeed, noteworthy.

AI and ML in App Development

Today, deep learning is the core of any mobile application, which has only been possible because of Artificial intelligence & machine learning.

With food supply apps that suggest food and restaurant choices based on our previous acquisitions and cab-hailing apps that update the location in real-time — we don’t even realize. Still, most of our daily interactions with these apps are driven by AI.

And this makes it a lot more pertinent to grasp the role of AI in the application development process.

So, what are AI and ML exactly?

What Robin is for Batman, Machine Learning is for AI — the perfect tag team.

While Artificial intelligence (AI) is a broader term that refers to the simulation of human intelligence being processed by machines, especially computers.

ML or the Robin here is a subset of AI that enables self-learning with the help of data it has been fed and then applies that learning in decision-making processes, without any external human help.

How is AI revolutionizing mobile apps?

As the world is leaning more and more towards ‘on-demand, consumers’ hunger for a better, more profound & highly personalized experience is also soaring.

Integrating AI in custom applications can lead to more intuitive and responsive products that provide a seamless, personalized, and I-can't-get-enough-of-it kind of user experience.

So what does all of this mean for your application?

1. Reasoning Abilities

Tesla’s Autopilot is the finest example of AI’s reasoning abilities as the next big thing.

The autopilot feature is entirely built on deep neural network principles as it uses cameras, ultrasound sensors and radar to perceive the vehicle's environment — and then act accordingly.

The sensors and cameras provide the drivers with a sense of the environment that is later processed in milliseconds to improve and reduce stress of the driving environment. And the Radar becomes really handy in light, dark and tough weather conditions to see and measure the distance around cars.

This promotes safe driving and in case of any possible casualty, it alerts the driver automatically. Besides this, the AI Autopilot feature is smart enough to detect obstructions on the road and street the car slowly when needed.

Amazing, isn’t it?

2. Personalized Experience

Ever noticed how you get hooked to Netflix at times — you start one show, wrap it up, find another one, wrap that one too and find your next pick.

And this cycle goes on forever.
But why?

You see, both Netflix and Amazon have employed AI + ML on their platforms, which evaluate user interests based on age, sex, and location and then offer the most commonly watch options (in their region) or shows of similar genre in the queue.

3. Understand Your Users Better.

Remember when you fire up your amazon app and search for anything — let’s say ‘running shoes,’ and after just a couple of minutes, you see other running gears such as joggers or sweatpants start popping up in your recommendation section of the app?

Well, it’s the ML doing its job there. You see, AI and ML are experts when it comes to browsing patterns and conduct for users.

Post studying the behavior patterns of every visitor, AI makes product recommendations and creates a customized shopping experience that makes them feel like the app was only produced for them.

This type of user interface results in greater customer satisfaction, higher revenue, and eventually, ROI.

4. Advanced Searches.

Reddit is already using ML for hundreds of millions of community members to improve search performance.

You see, the search bar is a crucial tool for Reddit users to find specific, search-centric content. Reddit leverages top-class search capabilities with Lucidworks Fusion AI + ML technology to make the search results more relevant for the users.

Thus, it proves that Machine learning helps you improve your application search, produce better and more contextual results, and make your search more intuitive for your users.

The algorithms of machine learning learn from customers' questions and prioritize their most important answers.

Improved Security In Apps.

Users can use features such as image recognition or audio recognition to set their biometric information as a security authentication step on their Smartphones — such as FaceID by Apple.

FaceID familiarizes itself with your various facial changes, such as growing your beard or hair over time, all with the help of machine learning.

Therefore, in addition to being a powerful marketing tool, artificial intelligence and machine education in mobile applications can streamline and secure app monitoring.

Google Duplex.

Google has been something revolutionary — something that can take the AI assistant game to the next level. They call it Google Duplex.

Recognized as a fully automated system, Google Duplex is an AI assistant built in your phone that can make calls for you, talk to the person on the other side and can even book appointments for you — in a natural sounding human voice.

According to Google, it understands "complex sentences, fast speeches and long remarks" which allows us to book appointments and reservations using Duplex.

Facebook’s Deep Text.

Zuckerburg’s team has also been a major player in the AI sphere since a long, long time.

Deep Text — an AI based tool developed by them to understand user behaviour on the social giant parses through the comments, posts, and other data generated, to understanding the user's context via learning how do they use language, slangs, abbreviations, exclamation marks, commas, etc.

They also use AI to make News Feeds a lot more relevant and match users’ requirements. This helps advertisers to deploy much more relatable content in their feeds.

Wrapping Up

While premature science fiction authors must have anticipated a lot more from AI of today’s world — but the rest of the world seems reasonably satisfied with what AI has achieved in all these years. And how AI can take the world in the future.

In the mobile app development sphere alone, AI has significantly impacted the experiences people get out of the apps. Although the integration of AI into the mobile app remains early, there's plenty that can happen.

You can shape your complete user experience using AI and use it in various mobile applications. Therefore, we must all see where AI can develop and experience mobile apps.