TOP-6 areas for using artificial intelligence

TOP-6 areas for using artificial intelligence

Today, artificial intelligence and all the technologies that are associated with it are developing at an accelerated pace. We first heard about such a concept as neural networks quite a long time ago, but few people imagined how serious an impact they would have on the life and work of modern people. At its core, artificial intelligence or neural networks — This is a mathematical model, device, program that works on the principle of a biological neural network. That is, they function in much the same way as the human brain, only the neurons here are artificial. But this does not prevent them from “learning,” “thinking,” “giving advice,” “developing.”

Now we will highlight a number of key advantages that artificial intelligence is endowed with, as well as those areas where it has found the widest application in practice. We will show you how to ensure the most stable and functional work with various neural networks without any risks and restrictions using a solution such as mobile proxies.

The main advantages of using artificial intelligence in practice

Before talking directly about the advantages of artificial intelligence, we note that the main task that its developers face today is — This is the creation of self-learning systems. Those who could extract meaning from the provided data, draw correct conclusions, and apply the acquired knowledge to solve new similar problems. Moreover, modern neural networks can respond to human speech, generate unique text and graphic content, and introduce real-time communication with the user. All these possibilities have led to the fact that various organizations and business representatives began to introduce them into their production processes, significantly simplifying the work of many specialists, as well as speeding up and automating the solution of an impressive list of everyday tasks.

Today, artificial intelligence is widely used in the field of business analytics, medical research, preventive maintenance of various systems and services, it is used in monitoring application performance, in intelligent data processing and more.

The main advantages of using artificial intelligence in practice are:

  1. Effective solution to complex problems. Artificial intelligence technology is based on machine learning and deep learning. This is what allows neural networks to approach problem solving the way humans do. That is, large volumes of data are initially processed, certain patterns are identified, and information corresponding to the user request is determined. In addition, this technology can work in absolutely any area, from compiling business analytics to conducting remote medical diagnostics, detecting fraud, etc.
  2. Choice of the most rational solution. Thanks to the fact that artificial intelligence is capable of processing huge amounts of data, it will be able to find the most rational solutions as quickly as possible. Moreover, modern neural networks are able to identify patterns and trends, provide recommendations based on the data obtained, and make fairly reliable forecasts. Thanks to this, you will have a solution on your hands that an ordinary person would simply not see.
  3. Increasing the efficiency of all internal business processes of your company. Unlike people, neural networks can work around the clock, maintaining their high performance. This means that they will cope well with similar and routine tasks, thereby relieving your specialists of increased workload. Entrust the solution of boring and time-consuming tasks to a neural network, thereby concentrating the work of your staff on more important areas of business that require creative thinking and a creative approach.
  4. Automation of various business processes. Quite simple machine learning algorithms will be enough to automate many production tasks with the help of artificial intelligence, making their solution faster and better. At the same time, you can be sure that all routine work is performed as correctly as possible.

Most of the specialists who have encountered artificial intelligence and its capabilities in practice note that it has quite impressive potential. And as soon as a new solution or direction appears on the market, it is immediately picked up by one or another specialist and begins to be used, further expanding its capabilities.

An example of this can be seen in the generation of images, namely at the moment when the transition from the GAN technique to diffusion models was made. Literally in the first days after this, there was a surge in the use of neural networks on the market, not only among specialists, but also among ordinary users who were interested in testing its work, experimenting, and creating something unusual and interesting. This is quite understandable, because before this GANs were mainly used exclusively because of deepfakes. But models such as GPT-3, and later ChatGPT, were the result of the transition between neural network architectures from RNNs to transformers.

Today, the high level of demand in neural networks is due to their wide functionality. So, with their help you can generate text, images, music and even create small videos based on the text description. All this functionality is hidden under such a term as generative artificial intelligence or Generative AI.

How widely is AI used in practice today

The fact that artificial intelligence and all the technologies associated with it will continue to actively develop in the future — This is no longer an assumption, but rather a pattern. At the same time, experts do not recommend looking into the very distant future, because everything in this area is changing very, very quickly. But if we talk about a closer perspective, it is worth noting that over the coming year there is great potential in the following areas:

  • Computer vision. Today it is somewhat behind the so-called natural language processing, which involves processing data written or spoken by a person. And by its very nature, computer vision is more complex to implement. It requires a more professional approach, taking into account a huge number of details: they are required much more than those that we specify to generate the same text or picture. But at the same time, his prospects are more than impressive. And this is not surprising, because by and large, human eyes — it is one of the richest sources of information in the world. That is, if neural networks can develop more actively in this direction, learn to professionally perceive not only written and audio information, but also visual information, the more modern and advanced systems will be created on their basis. Today, computer vision is already quite actively used in many areas, which we will discuss in more detail below. But if we manage to develop this technology further, then it will be possible to create unlimited autonomous systems, including cars, robots, and aircraft that operate without human intervention.
  • Computer games. The possibilities of photo and video integration open up unlimited possibilities for creating computer games based on artificial intelligence. With their help, gaming content will become more exciting. It will be difficult to predict the subsequent actions of the participants in the gameplay. Developers will be able to create an environment inside the site that will look as realistic as possible. That is, with the help of artificial intelligence it will be possible to launch games on the market of a completely new level, as realistic and believable as possible.
  • Development of systems to combat global problems. Already today, experts are taking active steps in such areas as the use of artificial intelligence in the fight against climate change, ensuring energy efficiency, and minimizing the negative impact on the environment. In this case, neural networks are planned to be used to control the most energy-consuming and polluting production processes in order to increase the efficiency of the resources used and minimize the negative impact on nature. Scientists are also already using artificial intelligence to create a large-scale system containing data on the production and distribution of food, which would become the basis in the fight against hunger in the world.

It would take quite a long time to list all the possible industries and areas where artificial intelligence can be used, because its prospects are quite impressive. Partially, those aspects that we have already discussed above have found their application in practice, but at the same time they continue to be improved, refined, expanding their capabilities and prospects. Today there are already millions of startups in the world that involve the use of neural networks, and many of them receive positive feedback and good funding.

But now we will not look into the very distant future. Let us highlight 6 main areas where artificial intelligence is actively used today. Those that do not require any complex developments from you. These are solutions that have already been tested in practice and which can be used in the work of many specialists, business representatives and others.

The most promising areas for the use of artificial intelligence

Now we will take a closer look at 6 areas where artificial intelligence has already become quite widespread. We are talking about such works as:

  1. Creating graphic content.
  2. Large language models.
  3. Computer vision.
  4. Transformer architecture.
  5. Video content encoding.
  6. Generate 3D objects and content for the metaverse.

Let's look at each of these areas in more detail.

Creating graphic content

In this case we are talking about converting text material into an image. That is, you describe what you would like to see in the picture, and the neural network directly creates the picture itself. Here you can get acquainted with neural networks that are created specifically for working with graphic content. But we would like to immediately draw your attention to the fact that in practice these works may not be as simple as they seem at first glance. The fact is that most modern neural networks are still at the learning stage. It is very difficult to explain to the application what exactly you want to see in the image. As a result, the pictures turn out unrealistic, not at all the way you would like to see them and what you originally had in mind. Therefore, one of the most relevant areas in modern engineering — This is industrial engineering. In this case, we are talking about teaching people how to write competent descriptions for neural networks – Promty.

But it is quite possible to assume that in the foreseeable future, working with neural networks will become easier, which is associated with training these systems and their improvement. For example, today there are already quite a lot of models that are available exclusively via API. This means that the entire model is launched directly on the server, and the finished image is returned to the process. But we would like to immediately draw your attention to the fact that most of the neural networks that work today in this direction allow you to generate images completely free of charge, but charge money for downloading the resulting content.

Another point that is worthy of attention — This is that, unfortunately, you won’t be able to get specific cases using artificial intelligence. The thing is that such content most likely was not used when training such networks. Therefore, in this case, you will need to create your own model, and only then make appropriate modifications to it. If you are interested in this aspect, then you need to initially choose a suitable model for yourself. Here it is worth choosing those solutions that are provided for training. But, to be honest, these works will not take you too much time. Practice shows that literally 3-5 hours will be enough to create your own unique neural network that will generate content specifically tailored to your specific requests. The learning process itself will consist of uploading photographs into the system that you have taken in the context of a particular case.

Also today there are more and more neural networks with which you can create video content. Here, of course, everything is more complicated than generating images. The main catch is that the objects will constantly change, literally from frame to frame. The creation of such material will require much more time and effort, but nevertheless, work in this direction is already being carried out very actively and is yielding good results.

Large language models

Along with creating graphic content, modern neural networks also do a good job of generating text. Such systems are called the Large Language Model, that is, “text within text.” If we analyze this market segment, the clear leader here will be OpenAI with its ChatGPT product. And here no one will have any complaints or doubts. The fact is that in this case, the developers managed to create a really cool basic model, capable of not only understanding the text, but also combining it, structuring it, and highlighting the main thing. In addition, this service can be used for translation, writing letters and other content. You can use it directly on the site or through the API. But you must be prepared for the fact that you will need to pay for each request in the full version of the product.

Today, large language models are gradually being introduced into an increasing number of business processes. They are used to build their own products, to facilitate work with them and clients. So, for example, the same ChatGPT can be taught to use your database and provide correct answers to the consumer audience based on the knowledge gained.

Large language models everywhere, and not only ChatGPT, are used to create text content to populate Internet sites. Neural networks are capable of creating quite professional materials, but so far only on the most common and popular topics. Just as in the case of generating pictures, neural networks cannot provide competent answers and recommendations on highly specialized topics. But on the other hand, you have the opportunity to complete their training yourself and receive an individual solution exclusively for your line of business. In this case, we recommend paying attention to the Large Language Model from Meta Corporation. At a price today they are one of the most affordable, their infrastructure and the code itself are quite large-scale.

The fact that artificial intelligence is capable of generating a variety of text content — this in itself speaks of its prospects and widespread demand even in the long term. It will be a great helper when filling out websites.

Computer vision

We have already talked above about computer vision as such and its distant prospects. But, nevertheless, this direction in artificial intelligence is already actively used in practice today. Few people know, but similar technology is already present in every smartphone, in most CCTV cameras operating in the world. Not a single video conference is complete without it. That is, today computer vision is present where visual perception is needed. With its help, objects are recognized in a video or photo, and also something is cut out from them, the background is changed or hidden.

So, among the most common solutions today, where artificial intelligence is actively used, we can highlight:

  • finding the necessary person, object, vehicle in the crowd;
  • identification of cancerous tumors on X-ray images, remote ultrasound examinations;
  • virtual trainer in the gym, able to suggest the correct posture when performing a particular exercise, etc.

And for this technology to work as efficiently as possible, a huge amount of photos and video materials should be loaded into the system. It is on these works, as well as directly on training the neural networks themselves, that the attention of a huge number of specialists is focused. Thus, at the moment there is an active transition from supervised learning models to self-supervised learning.

Today, there is already quite a lot of educational content, guides, and recommendations on the topic of computer vision. This means that if you wish, you can quite easily understand all these nuances and learn how to use this direction to your own advantage.

Transformer architecture

This is another area where artificial intelligence is used quite actively. In this case we are talking about the use of the so-called attention mechanism. Here the neural network is capable of understanding all incoming information in a certain sequence. So, if we are talking about text, the system will still understand its meaning, that is, there is no need to strictly monitor the sequence of words.

And the larger the model, the more information will be included in it and, accordingly, the higher the understanding of the context itself will be. For example, the same ChatGPT for its training uses a huge variety of data presented on the Internet today freely available.

Already now, transformer architecture is widely used not only in language models, but also in computer vision. But its most significant advantage is that it is able to combine both the first and the second, as well as easily and simply scale them. To use transformer architecture in practice, it will be enough to provide the system with small pieces of text or pictures. So, literally a couple of words will be enough, and for computer vision a piece of a picture, 16x16 pixels in size.

In most modern small neural networks using computer vision, neural networks of increased accuracy are predominantly used, while in larger-scale projects transformers are already leading. And one of the most significant reasons for this is that transformers learn more intensively and on a large scale, while models based on ultra-precise neural networks are already quite saturated.

Audio and video encoding

Imagine a situation where you need to save disk space or traffic during a video conference or stream. And here neural networks will also come to your aid by encoding video or audio. Thanks to this, the image quality will be higher, while the traffic costs will not change.

We should immediately note that such a solution is still at the development and testing stage, since this is a fairly new technology for today. Its essence is not to transmit the picture itself, but to encrypt its contents in the form of a text description using artificial intelligence. Next, this description is transmitted to another device, on which the neural network will automatically reproduce the image or video based on the received data. In practice, today such a solution can already be seen in computer games. In particular, video cards no longer render literally every 2-3 frame, but anticipate it. This significantly saves resources and also increases FPS.

Creating 3D objects and content for the metaverse

This direction should be of interest to those who are interested in VR/AR and related technologies. Today, this solution has found wide application in practice in such areas as virtual fitting of clothes. That is, you can sit at home and see how you would look in this or that new designer dress from online brand catalogs. This solution is already widely used by large retailers. This is truly what increases customer satisfaction and reduces returns.

Another area where 3D models built by artificial intelligence are actively used — This is interior design. You can choose excellent furniture, as well as related items for a particular room. At the same time, you can upload basic images of your room even with old furniture: it will not interfere with the neural networks. Some services will remove old furniture, others – will generate it at your discretion.

Another metaverse that is quite actively used today — This is the integration of three-dimensional clothing models onto user avatars or photographs. Moreover, you can “dress” wear designer clothes directly during a video conference. And at the same time, no one will guess that you are sitting in your home tracksuit.

Meta Corporation began similar developments more than 7 years ago. Their promise showed itself in practice literally in the first days after launch, which gave an additional impetus to development. And the further developments are carried out, the more clear it becomes that in the foreseeable future there will be a close combination of the real and virtual world, especially in the field of generating 3D clothing.

So what are the prospects for IT under the influence of artificial intelligence?

As you can see, there are quite a lot of areas in which artificial intelligence is already being actively used today. We also must not forget that this technology is developing at an accelerated pace, gradually turning into an increasingly more advanced solution. Today we can already say that the use of artificial intelligence in certain areas of professional activity, be it writing program code, creating pictures, text content, significantly increases the speed of completing these tasks by about 2 times. At the same time, the quality also becomes higher.

Understanding all this, many specialists working in the field of IT technologies are wondering whether they will lose their jobs or whether artificial intelligence will push them out of the market. In principle, such fears are completely justified, but most likely specialists will not be left without work: professions will simply transform, people will be engaged in solving more complex and creative problems than performing the same type of routine work. That is, the use of neural networks will become a significant advantage in the work of many specialists. They will be able to more clearly see the tasks facing them, quickly find answers to them, and identify mistakes made.

But still, we should most likely expect the most impressive effect from computer vision. There are already prerequisites for the fact that in the foreseeable future it will work together with language models. And the combination of visual perception and speech – this is something that opens up very broad prospects. So, for example, to create a picture, you can combine voice input, text, and some of your own drawings. This means that in the end you will be able to get a result that corresponds to your original idea to the maximum extent possible.

Therefore, in order not to waste time and not to remain somewhere on the margins of the profession, it is important today to gradually introduce artificial intelligence technologies into your work. And here are some tips:

  1. Try creating your own sample projects. This way you can see places that require additional elaboration and study.
  2. When you understand what exactly you don’t know, take advantage of certain courses and educational content. This way you will be able to obtain the necessary knowledge in the shortest possible time.
  3. Follow updates on the neural network market and pay attention to new developments. Perhaps they will become the tool that will be most convenient and effective in your work.

And the last thing we would like to draw your attention to is that it is optimal to work with neural networks through a mobile proxy. This is a solution that will provide you with a high level of anonymity and security when working on the Internet, and will ensure effective bypass of various regional restrictions. This means that you can safely use absolutely any technologies and tools in practice without any restrictions or risks of getting banned.

The only thing we recommend paying attention to is the reliability of the solutions you have chosen. Free proxy servers will be unstable and will not be able to guarantee your confidentiality or protection from unauthorized access. In order not to take risks and ensure maximum convenience and broad functionality when working with neural networks and the Internet in general, we recommend paying attention to mobile proxies from the MobileProxy.Space service. Follow the link for more information and current tariffs , test the product for 2 hours completely free.

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