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How is ML fueling another age of application advancement?
by Mrudul Shah, CTO and Cofounder at Technostacks Infotech

From the time of introduction of the computers, the primary objective of the evolution has been taking into consideration automating the tasks that won’t take a lot of time. Artificial intelligence serves as a term that is talk of the town a lot lately when it comes to task automation.  Various app development companies are aggressively using ML for web and app development.

In this regard, machine learning in apps has made automation possible. The machine learning market is projected to cultivate from $1.03 Billion in 2016 to $8.81 Billion by the year 2022, at a CAGR of around 44.1% during the estimated time period. 

You will come to know how advancements in machine learning technology have been influencing the age of application progression. Before we start discussing further, let us discuss some basic terms like artificial intelligence and machine learning.

Artificial intelligence refers to the intelligence and smartness established by machines, and it is the opposite of the natural intelligence displayed by animals, including human beings.

Machine learning in mobile app development serves as a branch of artificial intelligence and computer science that has been completely focused on using the data in the algorithms for imitating the way that humans are learning and improving accuracy. Around 58 percent of businesses have been using machine learning for running models in production. 

Model development in machine learning serves as an essential component of the growing field of data science. In other words, it can be explicitly said that machine learning, a type of artificial intelligence, will be making the software applications for becoming more accurate at predicting the outcomes without regular human intervention.

The Latest Development in the Machine Learning (ML) 

There have been the latest trends in web development and machine learning that has been impactful in businesses. Some of them are auto ml, full-stack deep learning, unsupervised machine learning, and reinforcement learning. In addition to that, there have been the latest advancements in artificial intelligence. 

Some of the sectors include the robotics industry, financial services, wildlife conservation, healthcare industry, and the automobile industry. Natural, artificial intelligence-based improvements include:

  • Quantum machine learning.
  • Responsive artificial intelligence.
  • Artificial intelligence-powered automation.
  • No artificial code intelligence.

Recent Use Cases of AI-based Apps

The important question is, what are the applications of machine learning? The popularity of ai in mobile app development is soaring by the day. There are some practical examples of the use cases, and they are as follows:

  • AI Applications in Navigation

GPS technology provides users with accurate and detailed information to improve safety. The combination of Convolutional Neural Network and Graph Neural Network makes lives easier. AI by Uber and many logistics companies have been looking forward to operational efficiency.

  • AI Applications in Gaming

AI creates smart, human-like NPCs that can interact with the players. The Alien Isolation game in 2014 uses AI that can help to stalk players throughout the game. ‘Director AI’ knows location alongside the ‘Alien AI,’ driven by sensors.

  • AI Application in Social Media

Applied machine learning considers likes, and the accounts can help in determining what posts explore tab. Artificial Intelligence, along with a tool called DeepText, allows Facebook to understand conversations better.

  •  AI Application in Marketing

Artificial intelligence (AI) applications have been becoming a marketing domain, and there have also been highly targeted and personalized ads. Chatbots by AI, Natural Language Generation, Natural Language Processing, and Natural Language Understanding analyze the user’s language. 

Benefits of AI concerning App Development

  • Simplifying the processes

Artificial intelligence, alongside cloud computing, has been paying together exceptionally well. Machine learning can be done on one device, and there are latency-insensitive things that get uploaded to the cloud. Machine learning requires plenty of trial and error for getting to the point and getting the desired output. 

The best approach has piloted the program internally first while developing App SDK. Developing machine learning is highly essential. Technical expertise, pricing, support, and data security turns out to be a vital factor. It is always significant for you to make sure that the cloud service provider has a demonstrated track record of avoiding security issues, challenges, and downtime.

  • Personalization

Machine learning has been helping with building the base on the information, getting access from the user behavior on the applications, and social media. The collected information will allow you to learn regarding the customer interest and how they are browsing your product. 

Around 87% of companies using AI plans for sales forecasting and email marketing will let you know the users’ preferences. The information gathered through the machine learning algorithms will be finding further use for the improvement and the shaping of the content of the product.

  • Improved user engagement

Some of the machine learning features can be applied to attract users to engage with the app daily. The c artificial intelligence-based virtual assistants can ensure engagement with the lost users and help the customers understand the product. 

Some machine learning applications for user engagement include Facebook and Amazon, and they have been using machine learning to manage smart requests and increase user engagement levels. Applications like digital assistants can be helpful for users writing a long email and making the call.

  • Upgraded security

Machine learning can ensure the streamlining of the security and authentication for any application. In this regard, there are certain factors like face detection, fingerprint access, biometric information, and voice recognition that will be working in the form of smart features helping in the detection of fraudulent actions and confirming safe access to private data. 

  • Programs debugging

SDK engineering ensures detection of the errors and fixing them without getting Command. So, the time of the development of the mobile app is reduced.

  • The easy accomplishment of the repetitive tasks

The worst part for every user is doing the repetitive tasks that require efficiency. So, when there is a need for doing repetitive tasks without regular human intervention, AI serves as one of the best fields for assisting you in the task.

  • Reading the mindset of the customers

The developers can get the opportunity to find out the past mistakes and experiences of the users using artificial intelligence. It comes with the combination of machine learning that can ensure helping the developers to read the customer issues and past mistakes. 

The global market for Artificial Intelligence has been expected to grow to $309.6 billion by 2026. The objective is the improvement of the interactions of the User experience while giving them the best experience possible.

  • Improvement of the revenue

Whenever the user gets the highest satisfaction from using your app hassle-free, your revenue will be boosted. It can be said that artificial intelligence improves the experience of the user. The more significant part of the retail brands will be serving better experiences and making the clients more satisfied. 

For example, please take a look at Google, where you can easily get the opportunity to know your customers and satisfy their requirements.

Future of App development with respect to AI

AI or Artificial Intelligence has changed the future of mobile application development. Also, it has been revolutionizing the development of mobile applications. The mobile applications developed with AI or AI-powered tools can provide a comprehensive, personalized experience. The AI can increase user engagement ensures a memorable user experience & long-lasting user loyalty. 

Visual search serves as the AI-powered technique that recognizes images.Automated Logical Reasoning is another field that has been prioritizing AI. Machines develop the ability to find solutions to complex problems. In developing mobile applications, AI helps analyze the user’s preferences, likes, and dislikes.

With AI, the developers get the opportunity of discussing the cost of hiring teams deployed for doing repetitive tasks, and AI ensures automating the tasks without any human input. That said, the applications naturally become cost-effective, quick & less vulnerable to human errors. 

Real-Time Translation is one of the boons of AI. An AI-powered translator working with the mobile application eliminates the need to install the application for language translation. 

AI has been offering a range of benefits with the Security with Facial Recognition. Facial recognition techniques are getting refined every day to serve as a security feature. 

How to Implement AI in a Mobile App?

Primary ways to incorporate the power of AI, machine learning, deep learning, and language processing into mobile applications include the Reasoning capability of AI, the Recommendation engine giving insights, and suggesting what to do next. Also, there is a need for assessment of the behavior of users on the mobile app.

Key Takeaways

AI will be shaping the future of Mobile Application Development. AI is opening the ways to innovate & accelerate the app development experience. The role of AI has been impeccable in shaping the future of Mobile Application Development. 

So, businesses need to hire the best machine learning development companies for app development with AI.

Author: Mrudul Shah

Bio: CTO and Cofounder at Technostacks Infotech, Mrudul Shah is passionate about helping start-ups and enterprises to achieve their IT business goals. His expertise is designing tailor-made solutions for their businesses that include IoT Product Engineering | Mobile & Web Solutions | Path-breaking AI/ML Solutions

 

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