The impact of artificial intelligence on search engines: what to expect

The Impact of AI on Search Engines: What to Expect

Search engines have greatly simplified the life of a modern person. In order to find out the necessary information, to find goods or services of interest, we no longer need to go to the library, shops, study magazines, books, spend time and effort on all this. It will be enough just to set the corresponding request in any of the search engines. But recently, various neural networks, including language ones, have been actively developing. What did it lead to? In theory, artificial intelligence should greatly simplify the life of a modern person. He will be able to understand requests, better understand complex issues, give ready-made answers, fitting them on one page, personalize the issue.

Now let's dwell in more detail on such a question as the influence of neural networks on Internet search. Consider advanced developments from search engines. Let's talk about how neural networks work for search engines. We will discuss the impact of neural networks on the future work of search engines, highlight a number of problems that intelligent search engines and their users may face in practice. Let's tell you why you need to connect mobile proxies to work. But, first things first.

Influence of neural networks on Internet search

Artificial intelligence has been used in Internet search for over 10 years. Back in 2010, Google developed a unique Rank Brain system that allows you to rank search results in order to promote the most relevant queries to the top of the search results. In practice, this technology was applied in 2015. Its task was to link individual words to determine the meaning of the query entered by the user.

Just a year later, a similar algorithm (Palekh) was launched by the Yandex search engine. Palekh made it possible to find pages, focusing not only on words, but also on the meaning inherent in the request. A year later, Yandex launched a new Korolev model, which was already trained to perform not only the analysis of headings, but also the entire content of the page.

Work on the development of search engines continues today. They are now based on an additional connection of modern language neural networks like ChatGPT. The so-called "smart search engines" are designed to select really useful and best content for users from what is presented on the Internet through the additional use of artificial intelligence algorithms. Today, such developments are already being implemented by corporations:

  1. Microsoft.
  2. Google.
  3. Yandex
  4. Baidu.

Let's take a closer look at the solutions that are implemented in each of these options.

Microsoft's Smart Internet Search

Microsoft is implementing the Prometheus neural network into its search engine. This is a corporation's own development, capable of recognizing requests containing hundreds of characters (up to 1000). For each of them, accurate and detailed answers are given.

To get the audience acquainted with its development, the corporation created a video presentation. It was based on the request: “In September, I am planning a trip in honor of the wedding anniversary. Where you can go from London by plane within three hours. Classical search engines are not able to process such queries. They are focused on simpler phrases, such as: "Not far to fly from London," "Travel Europe in the fall," "Romantic trip to Europe." That is, in such queries, more than three parameters do not intersect. In this case, this is a journey, a region, and then — distance (nearby), season (in autumn), for two (romantic). That is, to get an answer to the question “In September, I am planning a trip in honor of my wedding anniversary. Where can you go from London by plane within three hours? through a regular search engine, a person would have to set a whole cycle of queries, working through the information that he will receive every time.

What has changed in the smart search engine from Bing? All these parameters are already combined here. That is, we indicate that a romantic trip for two around Europe is planned in the fall. Geolocation, date, destination of the trip are given. Moreover, Bing has a chatbot on the right side that allows you to discuss additional details. So, you can ask the search engine to find for you a trip option to the sea coast, mountains, cities, or countries with an abundance of attractions. You can also additionally find out where you can book tickets, find suitable hotels, etc. This will greatly simplify the search for a suitable time option, save your time, since there is no need to process large amounts of data. You get a structured response that fully meets your needs.

Smart internet search by Google

Already today, the Google search engine is used by a neural network to generate responses to user queries. This greatly simplifies and speeds up network searches. That is, you no longer have to study a bunch of material from various pages at the top of the search results to find answers to your questions. The Google neural network will process your request, analyze the entire amount of material at its disposal, and provide you with just one page filled with text, pictures, links. If this option does not suit you, you can go down below and, thereby, go to the usual search engine.

Here, you can additionally set a number of queries to the search results in order to get the most accurate answer from the neural network. Another attractive feature of intelligent Internet search Google — performing comparative analysis. So, for example, if you are looking for a coffee machine, the system will offer you several options that meet your needs, add comparative characteristics to them, which will help you choose the best solution for yourself. Alternatively, the number of programs for making coffee, the number of servings that can be prepared at the same time, the capacity of the water / milk tank, the price can be selected as parameters. The system can also offer you a selection of stores where you can buy this or that model.

As you can see, everything here is also focused on minimizing the time that the user spends on the network in order to find the right solution for their needs.

Smart internet search from Yandex

Today, work is underway to introduce artificial intelligence into search engines in Yandex. So, today it is known that this product will be called Ya.LM 2.0. At the same time, this algorithm will be integrated not only into the search engine, but also into Alice.

Smart Web Search by Baidu

Does not plan to retreat from well-known global corporations and the Chinese search engine Baidu. Its developers announced the launch of their own analogue of ChatGPT. They claim that in the near future, the ERNIE neural network will appear on the market, which will generate messages to answer questions sent by the user. It is not yet said that this neural network will work as an independent product. They initially want to build it into the flagship search engine. Let's see what happens.

A little about how search engines work with neural networks

At the heart of any artificial intelligence is machine learning. Services that are designed to work in conjunction with Internet search are no exception. In this case, such a direction of artificial intelligence as Natural Language Processing is used, that is, natural language processing. Experts working in this field train neural networks to recognize natural human speech and automatically translate it into a language that a computer perceives as a request. Language models teach to work not only with audio, but also with textual information. They are designed to analyze large amounts of data, extract from them, retell, remove only the information that will best correspond to the text requests sent to users. Another distinctive feature of language neural networks – generating a response to a user request with simultaneous translation into certain languages.

To accomplish the task, experts collect huge amounts of data from Internet resources, social networks, books, magazines. Language models that process natural speech are used in their work by both online translators and voice assistants such as Alice, Siri. They also have tools for generating and recognizing text content. The same ChatGPT — this is a separate service developed on the basis of the most advanced GPT-4 model to date.

Today, many search engine companies are working to improve their products based on the additional connection to the work of artificial intelligence. They agree that neural networks can greatly simplify the work of a modern person in the network, speed up the selection of the right material.

How search engines will change in the future thanks to neural networks

All those updates that many search engines are actively working on today have just been announced. That is, they have not yet been implemented in practice. It is still impossible to say for sure what the result of their launch on the market will be. Initially, it is necessary to test the product in practice, and after that, make appropriate conclusions, make additional adjustments and improvements.

Now we can only highlight a number of points that should positively affect the connection to artificial intelligence search engines:

  • Providing users with more specific and accurate information. Connections to the neural network search engine will allow it to analyze quite voluminous queries, providing detailed answers to them. That is, in order to get an answer to a question of interest, the user will only need to ask one request, and not 5, 10, 20, which is relevant today.
  • The ability to use contextual search. A neural network with sufficient knowledge will help search engines directly understand the essence of a user request. If we return to the example of a trip that we cited above, then here the search engine already understands for sure that the event will take place in the fall, that it will be romantic, and the search geography is limited to 3 hours of flight by plane. And already on the basis of this, the user gives out for the corresponding answer.
  • Search personalization. Selection of music tracks based on previously listened content – this is already the norm for modern music streaming services. Also, none of the users will be surprised by the automatic search for posts on social networks based on previously viewed records. Similar technology can be implemented in search engines in the near future. That is, if you submit a request for the selection of coffee machines several times, the system will remember your preference and, in response to your subsequent request for the nearest stores, will give priority to those outlets where you can purchase coffee machines.
  • Predictive search. We are talking about the fact that in the future, neural networks will learn to predict your queries based on the search history. It can be thought of as the same recommendation feed for social media. Only it will now be based on user requests.

All this allows us to state with confidence that neural networks are quite capable of making fundamental changes in the search for information on the network, increasing its accuracy, reliability, speed, and making it more user-friendly. Already in the near future they predict the launch of releases from Google and Microsoft, so it remains to wait quite a bit. But in this direction, everything is as smooth as it might seem at first glance. The stability of the work and the reliability of the received data directly depends on the machine learning of neural networks. But here, developers may encounter a number of problems.

What problems can arise when integrating neural networks into search engines?

The more active the introduction of artificial intelligence into the life of a modern person, the more technical and even ethical problems arise. We highlight only the main points:

  1. Poor quality of personal data protection. The fact is that in the process of its training, artificial intelligence is based on a huge amount of data. It passes through itself incredible arrays of information, including personal information. And if it turns out that a hacking vulnerability is revealed in the search engine, all this data can become public. And in view of this, the trust in technology causes quite serious concerns among users.
  2. Reliability of information. We have already mentioned that the material created by people is used to train the neural network. What can't you find online today? Along with really high-quality, logical and reliable content on the Internet, there is a huge amount of fake news, stereotypical descriptions, materials that are scientific and proven in practice only by their presentation. This is true both for fairly narrow niches, in which there is not so much content, and for very popular topics — in order to stand out in a competitive niche, fake, but at the same time unique and beautifully presented content is often served. As a result, when using intelligent search engines, you can get one-sided, incomplete, or even erroneous answers. There is only one way to avoid this — training of neural networks should be performed exclusively on purified and diverse content, data that has actually been confirmed. But will it be put into practice? A question that raises completely justified doubts.
  3. Computing limits. In operation, any neural network requires quite impressive computing power and information storage. With subsequent training, these volumes will expand even more. And this means that there will be problems with their scaling. And here, the creators of search engines will face a serious question: how to optimize the system for artificial intelligence without compromising the quality of services and the speed of their work.


Despite the fact that work is being actively carried out in such a direction as the intellectualization of search engines, it is still difficult to say how effective, reliable, and the information provided will be. In many ways, the success of an idea depends on how much effort developers put into creating their services. They must be safe, based solely on high-quality and reliable data. That is, it is important to maintain a high speed of issuance, otherwise users simply will not use them.

We will keep an eye on this issue. It is still difficult to say exactly when all this will be available to ordinary users. But already today you can increase the efficiency, confidentiality and functionality of your networking, provide reliable protection against any unauthorized access. We are talking about additionally connecting mobile proxies from the MobileProxy.Space service to the work. For more information about this product, please follow the direct link

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