Oct 12, 2021 – Selim ÇEKAL
There may be some situations that require programming languages to be able to work with each other. As an example, we can give the cases where the project in two different languages was merged, and the newly added layer was developed in a different language.
Artificial intelligence applications can be developed in different languages. According to the ready-made functions and the ability of the programming language, the most suitable one for these applications is Python. The artificial intelligence application developed with Python can also be developed with Java, but considering the man/hours cost, it would be a better decision to make the application with Python.
There are several methods for the integration of the artificial intelligence application developed with Python to the web service developed with Java. Firstly, Python code can be run with some libraries to be added to the Java project and the result can be read. Another method is to read the results by running the Python code from the console with the Java code. These are just two methods that will solve our problem on the subject.
When it comes to artificial intelligence and the ability to view its results on a web platform, the most important problem that comes to mind is time. How can a web platform using artificial intelligence be able to produce accurate results without making the user wait too long? The most important feature of websites is to present the result to the user as soon as possible. Artificial intelligence applications, on the other hand, are applications that produce results after heavy operations using thousands or even millions of data through various algorithms. Therefore, they give results in a long time.
It is possible to add such an application to the Java web service and present the result to the user on the web, but it is a big problem in terms of time, which leads to losing the user. One of the most significant reasons for the loss of users is the late response of the website. Naturally, this is an undesirable result. What needs to be done here would be to resort to technology again.
The rapidly developing technology offers us good opportunities. The development of 2, 4, 8 and the number of processor cores that continue to rise are just a few of these good opportunities. Thanks to the technology, the development of programming languages does not delay.
We can solve the time problem of the developed artificial intelligence application with the multiprocessing method. A computer with a multi-core processor is enough for this. It is possible to shorten the time by distributing application processes to cores. Thus, the application will respond to the user in a shorter time depending on the number of processors and cores.
This may not be enough. More data mean more processing and therefore more time. So, what can be done in this situation? The time it takes to show the results to the user will increase even more. But, technology and software will not stop here, they will help us. Thanks to the libraries developed for Python, if the model used for artificial intelligence is run at once and made accessible to the system, no matter how much data is used, the application will not run this model from the beginning every time and will give users results in a short time by using the model it has created once.
As a result, users who get the answer they want from the artificial intelligence application as soon as possible will be satisfied with the service provided. Software developers, on the other hand, will have the experience of taking a new step into the future of technology with the pride of having done their job in the best way possible.