AI in Mobile Apps: Latest Trends

How artificial intelligence is transforming our interactions with smart devices

Basics 101: What is Artificial Intelligence? 

At its most basic, Artificial Intelligence [AI] uses computer systems to simulate human intelligence in order to perform a range of tasks which would otherwise be performed by people. 

Digital devices using AI tools are able to perceive their environments, analyze and collect data.  They can also take actions that optimize task processes and facilitate goal achievement. 

AI-powered computer systems can perform situational and environmental analysis, language translations, financial transactions, voice recognition, visual perception and self correction.

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AI Mobile App Development

The rapid growth and wide implementation of AI technologies have enabled new technical possibilities and business opportunities for mobile app development. 

Running on machine-learning computer models, AI technology uses flexible algorithms that establish and maintain seamless and intuitive mobile user experiences.    

In this article, we’ll explore how AI is revolutionizing mobile app development by changing the way developers, businesses and end-users interact with each other. 

Chatbots 

Chatbots use AI to offer optimized task performance and an improved customer service experience by remembering and learning from the user’s actions and personal preferences. 

As customers expect more personalized experiences from digital products, retail giants like Amazon are using AI chatbots for better customer services and unique user recommendations. 

From English language learning, financial advice and fitness tips, apps like Andy in English, Digit and Lark are successful examples of mobile apps using integrated AI-powered chatbots.

Essentially acting as virtual assistants for companies, chatbots can benefit any online store or business by answering customers’ questions, collecting feedback and boosting brand loyalty.    

Machine Learning [ML]

Machine learning is a crucial feature of AI technology. It’s based on the idea that machines receive and analyze data and then teach themselves how to be better at their specified tasks.

By processing enormous data sets, AI systems apply accurate knowledge that allow them to excel at facial and speech recognition, financial forecasting and language translations. 

The global machine learning market is expected to reach $20.83 billion by 2024. With Internet of Things devices being smartphone-controlled, the market potential of ML-powered apps is huge. 

Popular mobile apps like Tinder, Snapchat, Google Maps, Oval Money and Netflix have all integrated machine learning tools to offer intuitive, functional and user-friendly experiences.  

Natural Language Processing [NLP]

Natural Language Processing [NLP], another branch of AI, aims to create digital devices that can process and respond to voice or text data in the same way as humans do. 

Mobile applications of NLP can be game-changers for people with physical disabilities as they could enable seamless, hands-free and verbally-controlled device access and operation.

NLP has been successfully used for years in virtual assistant apps like Apple’s Siri, as well as GPS navigation applications, allowing users to verbally ask for destination directions.  

Apart from advanced speech recognition capabilities, other uses of NLP include smart spam filtering, identifying fake news, sentiment analysis, job recruiting and content creation. 

Biometrics

Biometrics technology can detect, measure and analyze human behavior, as well as the human body’s structure and shape through smart devices like phones and watches. 

Apple’s release of the iPhone 5s in 2013 pioneered the way for biometrics integration within mobile devices through its first-time use of a fingerprint sensor on a smartphone.  

The benefits of having biometrics technology within mobile apps include speedy identification and stronger cybersecurity, improved user experience and more efficient data management. 

From banking applications to password vault apps like 1Password and Dashlane, biometrics technology can offer next-level security for a wide range of uses and requirements. 

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Image Recognition

Recent advancements in AI-powered machine learning and vision models have drastically improved the performance and mobile application potential of image recognition technology.

Smartphone apps with image recognition technology are able to combine camera input data and AI algorithms to process vast visual databases and provide users with useful information.

Google’s Lens app enables users to photograph anything from food, flowers and buildings, and then receive useful links, articles and other relevant resources based on the image captured. 

Addressing the needs of blind and visually impaired people, apps like TapTapSee use a smartphone camera and voiceover function to identify out loud whatever the camera points at. 

Emotion Recognition

Emotion recognition is another fascinating aspect of AI development. It relies on the capture and analysis of subtle body language variations and vocal pattern intonation to read human emotions.

Through incorporating AI and ML into mobile applications, developers can benefit from efficient sentiment analysis by accurately capturing and making sense of human micro expressions.

Data acquired by emotion recognition tools can help companies define marketing strategies, enhance customer satisfaction, develop new products and identify product upgrade needs. 

This technology allows developers to create immersive digital products that are able to automatically adjust their virtual environments based on the user’s emotional state in real-time.  

Big Data

Big Data refers to large and dynamic datasets that can be processed using AI-powered computer systems to reveal trends, patterns and associations linked to human behavior.  

The advantages that AI provides for speedy and efficient data management cannot be overlooked when it comes to developing powerful, user-friendly and data-driven mobile apps.  

The large volumes of raw or unstructured data collected from millions of mobile app users require high-end analytic processes that can offer companies unprecedented business insights. 

Benefits of Big Data in mobile app development include advanced analytics of user experience and social media, real-time availability of data, as well as customized marketing campaigns.   

Internet of Things [IoT]

The Internet of Things [IoT] essentially means billions of internet-connected digital devices around the world, processing large data volumes using AI algorithms and machine learning. 

Whether it’s a lightbulb or a child’s toy, as long as there is a solid internet connection, almost any object can be turned into an IoT device, capable of data transmission and remote control. 

Paired with mobile applications, IoT devices establish smart digital environments that empower users with real-time synchronization and automation, in addition to remote operation ability.  

IoT-based mobile apps are cost-effective and provide unique knowledge of client behavior and enhanced productivity, as well as safer workspaces and improved customer experience. 

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