In today's world, AI is a rapidly evolving field. It started with assistants for individuals and businesses that don't require much effort, time, or resources, but now neural networks are taking over more and more aspects of society. Gradually, people began to fear this assistance, as it often seems that artificial intelligence is much smarter than any human, but is AI truly that advanced? Does he really understand everything, or is it just an illusion?

The first and simplest thing that comes to mind is translation. But what is a translator? It's someone who understands another language and can adapt a text or conversation from one language to another.

It seems like a straightforward task that AI can easily handle. However, there are some hidden details:

1. Understanding culture.
The culture of each country is different, has its own characteristics, which manifest themselves in the behaviour of the speaker, views, attitude to time and much more. One of the tasks of a linguist is to understand and read emotions and subtexts, messages that a person has in mind without saying them directly.

2. Creativity.
From the first point comes the next. A human being is able to think deeper than artificial intelligence, to be aware of how language works, and this allows a linguist to understand sarcasm, irony, and to respond appropriately.

3. Language intuition.
Thanks to understanding the deep levels of language, a human being has developed the so-called "language intuition", and can consciously break established rules (for example, in art) so that a native speaker understands what is being said.

Neural networks are learning at a rapid pace, creating competition for humans, and of course, there's a reason for that. AI has its advantages that make it difficult for humans to compete with:

1. Speed.
It's no secret that machines are much faster than humans, and this is one of the main factors in the race between linguists and neural networks. Artificial intelligence processes information in seconds, allowing for quick access to information.

2. Information volume.
Along with high speed, AI processes huge amounts of information that the human brain is not always ready to handle. The machine can easily provide large and detailed answers to any questions.

3. Accuracy.
The neural network's answers are direct and follow the rules of the language, and they are based on patterns, which provides a good foundation for understanding the topic as a whole, rather than for in-depth knowledge.

If we compare language models and linguists, we can see that a human is focused on the process, while a machine is focused on the result, not its effectiveness, but its volume and speed. The human brain and the robot's software operate in completely different ways, and no matter how "perfect and intelligent" the latter may seem, the linguist will always have an advantage due to:

• 1. Deep understanding, which involves knowledge of rules and their connections, exceptions, and their historical origins.
• 2. Mental representation. This means that a person is aware of the connection between language and culture, and is able to infuse emotions, feelings, and the historical experiences of a country into their writing or speech.
• 3. A combination of reflection and intuition, which allows a linguist to truly appreciate the beauty of language and understand it on a deeper level, enabling them to communicate more effectively with others.

However, it is important to recognise the limitations of artificial intelligence, as it may not always provide a deep understanding of a topic. Instead, it may offer a more straightforward representation of the subject. While the process is important to humans, the neural network produces a result using:

• 1. Static patterns, which means that the model does not know the rules, but calculates the probability of words and constructions following each other based on the resources available in the databases.
• 2. "Mathematics", which means that it does not have personal experience, emotions, or awareness, but can operate on so-called mathematical vectors and formulas that have been loaded into it by the developers.
• 3. Generating plausible text based on template data and mixing it from different resources.

And yet, as we come to a conclusion, it is worth saying that linguists can not do without neural networks now, just as neural networks can not do without linguists. While artificial intelligence needs to correct errors, add necessary templates to the system, fine-tune models on high-quality and up-to-date data, and evolve the ethics, fairness, and cultural aspects of the conclusions that the machine makes, humans need tools for primary processing and analysis of voluminous information, automation of routine tasks, and generation of ideas for research work.

In summary, it can be understood that the neural network does not know the language as such, if we are referring to human meaning, but it skilfully mimics this knowledge thanks to the developers and linguists. Despite this, artificial intelligence has already become an indispensable tool for linguists, helping to improve the efficiency and effectiveness of work related to natural language.