Mobile applications and neural networks

Today, mobile devices are used everywhere – more than three billion people around the world actively install and use applications. This is the conclusion reached by experts from Statista, the world’s leading statistics portal. At the same time, the rapid development of new technologies makes it possible to improve artificial intelligence (AI), which simplifies and optimizes various areas and processes.

Many experts have no doubt that in the near future applications will learn to fully self-learn using neural networks and become dominant in the IT market. Currently, the introduction of machine learning already allows you to expand the functionality of applications and improve the quality of their work.

The neural network reproduces the principle of the human nervous system, including its ability to self-learn, taking into account the accumulated experience. The principle behind it helps AI to make fewer mistakes when performing its functions.

Neural learning is actively used in the development of software for the recognition of photographs, videos, etc. This area of ​​AI use is called “computer vision” and is a technology that detects, tracks and classifies objects.

Prisma, Snapchat and FaceApp are examples of successful use of neural networks, which have managed to achieve impressive results in image processing (for example, FaceApp is able to artificially “age” and “rejuvenate” people, change their hairstyle, apply makeup, etc.).

A number of modern smartphones have an image recognition system that automatically sorts photos of people with similarities into a separate folder. Such a program uses API analysis of human faces, processes data and organizes photographs based on the information received. If the user notices and fixes an error that the application made, it takes into account the changes and thus continues to improve.

There are several key opportunities, as well as development paths that the introduction of artificial intelligence opens up:

• Speech recognition

Neural learning is applicable not only to images – its potential is very great, in particular, it extends to work with audio and voice recognition (thus Google and Yandex developed voice assistants). Modern AI-based speech recognition software is rapidly improving and evolving. For the foreseeable future, they will more effectively adapt to users, thereby increasing comfort and ease of use.

• Creation of chat bots based on neural network training

For example, during a call, the system will collect and process information about a client, so that later, using a bot, build a convenient communication model in a language familiar to him.

• Marketing optimization

For many users, intrusive advertising is annoying, but neural networks will help users forget about this problem, and advertisers will significantly reduce meaningless expenses. The technology will independently study the target audience and select individual marketing moves and strategies for it.

• Tips, predictions and recommendations

Modern technologies allow social networks to study video and audio content of interest to users, and then select and offer them materials for listening / viewing. For example, this is how YouTube video hosting works, where users find about 70% of videos thanks to the system’s recommendations.

The main task of neural learning is to bring the principle of operation of the application as close as possible to the user. AI is nothing more than a well-trained algorithm aimed at recognition and analysis.

For a business, the implementation of neural networks will help with solving daily routine tasks, simplify communication with the target audience, and will make it possible to achieve significant success in the field of customer service and other operations, including process automation (for example, billing in real time).

Neural network methodologies are increasingly being used in various fields of activity, from scientific research to business applications and data analysis.

The use of AI in mobile devices is closely related to the use of personal assistants, which study user habits in the application and identify their preferences.

New technologies enable marketers and app developers to more quickly understand the behavior of target audiences by analyzing the actions, preferences and purchases that potential customers make.

Implementing artificial intelligence in applications has many benefits as it opens up new opportunities for them:

Data mining and automated thinking
These applications use algorithms to solve specific problems. For example, Uber uses this technology to optimize the route and help the driver to get to their destination as quickly as possible.

• Referral service

It is one of the most popular AI applications in mobile applications and is suitable for almost any task. The system monitors the choice of users and enters them into the learning algorithm, after which it generates recommendations that are likely to be of interest to the audience.

• Exploring Behavior Patterns

These platforms learn user behavior patterns to make the next session more successful. For this purpose, natural language processing can be combined with machine learning.

A particular use of the technology is the detection of online payment fraud. The algorithms go through orders / purchases on the card, form a behavioral pattern and, at the time of the transaction, reveal that the user has made a purchase that does not fit into the framework of his usual behavior.

Artificial intelligence can predict shoppers’ preferences in online stores, can personalize ads, and is great at delivering 24/7 customer service.

The digital market is developing rapidly, so the introduction of neural networks into applications is a matter of time. Providing mobile access to data, integrating applications with different systems, and implementing an API-based architecture will increase the company’s chances in the competition and help it better understand its target audience.

Businesses that actively use artificial intelligence in their business processes are reaping tangible benefits through cost savings and improved efficiency.

AVADA MEDIA is engaged in software development, as well as the integration and training of neural networks. Our specialists create reliable and stable artificial intelligence-based applications for projects from various fields. We are focused on the result, but at the same time we remain flexible in the choice of technical means and ways to achieve it.