Since artificial intelligence and related services have become pervasive (which actually has not been a long time), different uses have been made in various fields. Editing and creating images and videos, designing and ideating for different objects, writing different texts, and question and answer, and many other uses, including thousands of uses of artificial intelligence. In the meantime, many people have shown more creativity and with a little imagination, they have been able to find interesting and new uses for this new technology and combine it with various businesses and professions.

One of the professions and industries that we want to discuss the impact of artificial intelligence on is the automotive industry, specifically car remapping or ECU tuning. Currently, some automotive companies or other businesses related to cars and vehicles use basic artificial intelligence services such as chatbot question and answer and customer guidance (similar to a limited version of ChatGPT) services. The way these services usually work is that common questions and their predefined answers are given to these services, which then guide the customers. This service is very useful for websites that sell a large number of products.

❓But is that all?! So what are the more creative applications of artificial intelligence in the automotive and remapping industry? Are there other uses as well?

The answer is definitely yes, but to give a more precise answer, we need to explain a few very broad concepts in artificial intelligence in simple language.

💬What is machine learning?

What is Machine Learning? Machine Learning, or ML for short, is one of the subsets of artificial intelligence. Artificial intelligence, in its simplest definition, is the integration of sciences to make machines more intelligent. Now, Machine Learning is a set of methods and techniques within the realm of artificial intelligence definitions. Within this, there is also a concept called Deep Learning. Deep Learning is a subset of Machine Learning (see below) and refers to methods and algorithms that help in the development of artificial intelligence by using and drawing inspiration from the neural network of humans and other living beings.


Currently, automotive companies are offering very innovative designs using artificial intelligence. In fact, they modify and optimize some parts of their designs and calculations using artificial intelligence, personalizing the designs. In fact, this is the same work that is done in many other industries and professions (such as interior design).

But what is needed to make the designs offered by artificial intelligence more personalized, optimized, and practical? The answer: it requires more and more accurate data for machine learning. Now, keep in mind the point we made; the new question is: How can we use artificial intelligence for ECU tuning or remapping (we can even choose to call it "i-map"!)? Is such a thing possible?

Technically, yes. It is possible, and in an optimal scenario, this can have a low margin of error. We will explain how to reduce this margin of error for you in the following.

Currently, there is no company or service that provides AI remap (i-map) and the reason for this is that, according to the definitions we have mentioned, for a proper and very low or even zero error percentage i-map, we need machine learning. Integrating this framework with programming and also the science of remap requires significant time and a database of original ECU files. Given the relatively short public release time of artificial intelligence services, the necessary time to complete all the pieces of the AI remap puzzle has not yet been provided, and the existing cases, as explained above, are only pre-planned and ready dumps (such as the same frequently asked questions mentioned above). So if you are excited to use i-map, you need to wait a little longer and give time to this system for further and better development and lower error percentage.

💬Is AI Remap good?

If such a system is created by any company, as mentioned above, the important point is that this system should be based on accurate and fundamental information, maximum accurate information should be given to the system, and also supervision and double-check should be done by a technician (human supervision is necessary until this innovation reaches a safe point). If these conditions are met, you will actually be dealing with a regular remap and there will be no need to worry. In fact, it can be said that with the existence of i-map, we may even have more precise and less erroneous files, because if we review the reason for the need for such innovation with ourselves again, it reminds us that the whole reason for doing this, at least initially, is to get the job done faster. In fact, this means that a good i-map should be able to do the remap in the shortest time and then with the expansion of the system database and the machine learning process, other high-flying analyses and other strange and wonderful work can be done! So in summary, as good or bad as the remap is, the i-map is just as good or bad!

💬Stage Tuning with AI Remap:

❓Another question that arises is whether it is possible to do stage 2 and 3 tuning with this technology?

This is also possible with AI remap, but the issue is that completing the required data for stage 2 and 3 tuning requires more time and certainly more difficulty, as unlike stage 1 tuning in two similar cars (which can be a good exercise for machine learning), in stage 2 and 3 tuning, due to the use of aftermarket parts, this becomes more difficult because here the final files of two identical cars that have been staged 2 with different aftermarket parts will not necessarily be the same and there will be minor and major differences, in which case you cannot teach these two as a repeated file to artificial intelligence.

🏁The Future of Tuners:

After the public release of artificial intelligence and related technologies, in many discussions, the disappearance of many jobs was predicted. Many predicted with great precision (in their own view) which jobs would disappear or become less prominent. But in our view, this is not the whole story. Such predictions with such precision require the examination of many parameters in various dimensions. We explain the issue with an example:

At the time of writing this article, there are many artificial intelligence services that do the same work that many engineers do. For example, in architecture, there are AI services that, with a photo of your house, provide you with very good 3D design proposals. But does this mean that all architects are going to be unemployed? No!

So does this mean that no danger threatens the job of architects? Again, no!

In fact, which professions and individuals are at risk with the expansion of artificial intelligence largely depends on themselves. The same example of architecture mentioned above requires an executor to implement the final design, address any final issues during execution, and have final oversight of the project implementation. But this is only in this specific profession. What we mean is that even if artificial intelligence enters many areas of human life (which it can), there will still be gaps and issues in implementation and before or after deployment that will require the intervention of a technician. Perhaps even without any issues, with the intervention of a technician and their collaboration with artificial intelligence, the final project may be of higher quality. What we mean by stating this is that with the entry of artificial intelligence, it is not necessary for someone to lose their job with certainty or to easily gain a specific advantage. In fact, this depends on individuals and how they utilize artificial intelligence. By generalizing the points mentioned to the profession of remapping, it can be said that the profession of tuners is not necessarily at risk with the entry of artificial intelligence, as the important factor will be how tuners align with this technology, which will either jeopardize their profession or advance their occupational and financial position.     

📍If you have any question, feel free to contact us at: support@caracaltech.com