Guest Post : These are the ways mobile devices can use AI

Machine learning, Artificial Intelligence, and many more disruptive technologies seem to have permeated the tech world like never before; everything feels so enhanced and improved from smartphones Siri to self-driving cars. Nobody knew that the term once used to define the machine’s ability to simulate human intelligence will boost up such an extent.

Gone are the days when smartphones were limited to being cloud-based and internet-dependent. With the emergence of AI, technological expansion seems to be accelerating at a fanatic speed. What’s more, machines are turning out to be increasingly more fit for performing human-like undertakings and change in accordance with new sources of info.

Another fascinating part of AI

Another part of the AI that is neglected nowadays is incorporating AI. It is imperative to realize that arrangements and numerical relapses are required to upgrade learning with satisfactory oversight. On the off chance that basically, it is the capacity to recognize designs in floods of sources of info that AI-empowered gadgets required to learn with no sort of oversight.

Regularly known as a bizarre innovator, AI has been offering gigantic assistance to mobile app developers worldwide in making the ferocious rivalry a problem-free procedure for clients. According to sources, by 2025 the worldwide market worth of Artificial Intelligence is going to cross $89 Billion. When it comes to enhancing user engagement and business growth, AI is always useful. AI solutions are helping in gearing up and understanding user engagement based on user behavior patterns.

Further below I would like to mention how AI is used in mobile app development technology. One of the finest and most common examples considered to date is pattern recognition. Have you ever wondered what facial recognition expression or that tone of voice indicate? in applications, AI utilizes design acknowledgment, aside from not at the degree of complexity that human-like cognizance requires. Now imagine you find a particular pattern of lines that indicates a picture of a dog whereas another looks like a cat. Artificial Intelligence has the potential to recognize patterns in data, words, phrases, and images. The most interesting aspect here is that it can pick out the habits of the human user from the data it collects.

AI to improve iOS app development

Trial and error are the simplest forms of this intelligence and there are times when programmers have to try various attempts at random to achieve a single purpose. When found right, it automatically stores the solution for future use. And in case, if such a problem surfaces again, it won’t hesitate to recall the previously stored solution. Apart from this, unlike ordinary machines, AI enhances the interaction process. More specifically developers can enhance reasoning by drawing appropriate interferences to the situation. Lastly, the combination helps end-users to attain some predefined solutions or goals like none other.

Some of the best AI apps for iOS include – Replika, Airplay, Seeing AI, Cortana, ELSA, The Roll, and so forth.

Productivity Apps

One of the finest examples of productivity apps employing AI to streamline and create efficiencies include Google’s “G Suite” and Microsoft Office 365. To be progressively explicit, clients of this innovation can get to auto-produced reactions for email answers which just require a short reaction.

Throughout the years, Microsoft has been including AI innovation, for example, Office Graph and Delve. For the individuals who have no clue, the office chart is the basic framework that accumulates information about key communications among clients and “items, (for example, records or other substances). Dig causes clients to slice through the messiness of data and see the things generally significant and pertinent to the first.


Last but certainly not the least, chatbots are the finest example of the popularity of messaging apps fueled in areas like customer support for technologies. Chatbots succeed best in conditions where their application can be obliged. Why? Since they depend on AI and regular language handling (NLP – where PCs can process the message as people would). At present, if you somehow happened to solicit something outside from the domain of the bot’s preparation, it is presumably customized to either allude you to a human administrator or answer “I’m heartbroken, I didn’t get that.”

Attendant applications, for example, Mezi for movement are a genuine model. This application utilizes AI and NLP to make sense of the inclinations of clients and offer proposals for movement, design, or blessing thoughts they may like.

Salesforce’s “Einstein” is an incredible case of big business innovation.

Reasons AI is opted by a wide range of industry verticals

Not just mobile application development, Artificial intelligence is being widely used in the plethora of industry. Have you wondered why?

  • Improving Search experience – AI improved the client experience while looking through the client’s connected items. This innovation added another approach to recommend the client while looking. The mix of ML and picture acknowledgment in AI portable applications took the client experience to the following level. New patterns have been set after the voice acknowledgment innovation amalgamation into the framework.
  • Forecasting advertising – Marketers need to gather, keep up, and examine tremendous pieces of information. It requires some investment to keep up with client data. In this way, AI is here for managing client information, coming about to improve deals. Simulated intelligence controlled applications support in exploring and breaking down the market.

AI technologies in mobile app development

  • Pattern recognition – This is not new but that doesn’t mean it doesn’t foresee growth opportunities in the upcoming years. Fortunately, mobile app developers aren’t ignoring the growing interest of technology in an unconventional way. Now how this works, you may be wondering? In patter recognition, with the help of machine learning algorithm patterns can be recognized hassle-freely. It is more or less a classification of data based on the knowledge that has been gained or extracted from representations. If simply put, pattern recognition involves classification and cluster of patterns. Right from recognizing and classifying unfamiliar objects to identifying patterns and objects even when partly hidden, pattern recognition works such wonders.
  • Biometrics – This is another interesting pointer that deals with factors such as recognition, measurement, and analysis of the physical features of the body’s structure, form as well as human behavior. Now you must be wondering how can an organic interaction establish between machines and humans. Simple, touch, image, speech, and body language. Mainly used for the purpose of market research Biometrics works wonders.
  • Natural language processing & text analytics – It may quite interest you to know that establishing effective communication and clear among humans is a tricky venture. And as for machines, in order to process information is altogether a different story than a human brain; which means it is more complex and trickier. Natural language processing and text analytics come to the rescue! Being a sub-discipline of AI, the technology surely helps in converting text to data as well as systems to communicate ideas and thoughts in the clearest manner. Used by companies like Attivio, Automated Insights, Cambridge Semantics, Digital Reasoning, Lucidworks no wonder the tech makes it to the list.
  • Optical character recognition – OCR is one such image processing technology that provides a convenient way to extract text from paper documents and turn them into digital format. OCR simplifies the entire workflow as it processes tremendous amounts of time and resources to capture thousands of documents. By saving such time, the technology certainly boosts your productivity and end up optimizing business workflows to a great extent.
  • Speech recognition – As the name implies, speech recognition is used to convert and transform human speech into a useful and comprehensive format for computer applications to process. The transcription and transformation of human language into useful formats is witnessed often nowadays and is growing rapidly. Companies like NICE, Nuance Communications, OpenText, and Verint Systems offer speech recognition
  • Face recognition – Unlike others, facial recognition is the enhanced application of image analysis technology. The input is an image or video stream whereas the output is an identification or verification of the object that appears in the image or video. The process comprises of facial detection and tracking, facial alignment, feature extraction, feature matching, facial recognition.
  • Image recognition – The term refers to the process of identifying and detecting a feature in a video or an image. Image recognition helps the process of image searches greatly as well as to detect license plates, diagnose disease, and study personalities.

So that’s all for now, keep watching the space to know more regarding the same.

Writer note: Joanna is a Technology Analyst at Tatvasoft Australia – A leading Mobile app development Company in Australia, She has been working for five years in a Technological domain. Her work across multiple disciplines broadly addresses the narratives of techno experience. you can find her on twitter @BarettoJoanna

Guest Post : These are the ways mobile devices can use AI
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Guest Post : These are the ways mobile devices can use AI
Machine learning, Artificial Intelligence, and many more disruptive technologies seem to have permeated the tech world like never before; everything feels so enhanced and improved from smartphones Siri to self-driving cars.
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