Top 8 Programming Languages For Artificial Intelligence Projects

Artificial Intelligence

5 MIN READ

April 22, 2021

AI Programming Languages

With a plethora of use cases and opportunities around the corner, Artificial Intelligence has successfully penetrated through businesses. However, the scope of AI indicates that we have witnessed a minor percentage in comparison to what’s next in line. So, what can be the procedure to extract all the benefits of Artificial Intelligence? Well, choosing the best programming language for Artificial Intelligence projects will help a lot!

Every language has its own strengths and weaknesses, and they offer separate features. It’s you who decides which features suit your requirements the best for Artificial Intelligence Projects.

best programming languages for Artificial intelligence Projects

Programming Languages For Artificial Intelligence

  • Python

You can simply consider Python as the forerunner of all other languages right now. The reason for this breakthrough popularity is the simple syntax used in Python. Furthermore, the simple syntax will allow you to spend much more time on planning the core structure, which is why Python is an ideal choice for Machine Learning processes. 

With ready-to-use libraries, object-oriented programming, easy testing, and faster development, Python is your go-to language for customized AI solutions. The best part is that Python can be easily integrated with other languages for added convenience, like JAVA. Now, simplicity and a huge open source community support are what makes Python the best programming language for Artificial Intelligence projects. 

  • LISP

Now, the huge credit of what we are witnessing from AI goes to LISP. It is the oldest language used for AI processes and the second oldest language overall. LISP has always been considered as a tool for leading companies in AI with its enlarged scope of turning thoughts into reality. The language differentiates itself from other AI languages by eying precision. 

However, the use of LISP language is more on the downward side due to its innumerable flaws. The language is well-known for implementing wonders and is still used for logical solutions, which brings it to the list.  

  • R

When you think of statistical processes in programming, R will definitely strike your thoughts. The high efficiency of the programming language separates it from others in the list. More than the general abilities of R, the extended packages are the ones to consider. Packages like Gmodels, RODBC, OneR, and Tm allow huge support for Machine Learning processes.

When these packages are coupled with a wide range of libraries, the capabilities of the R programming language reach new heights. The programming language is preferred by top AI companies for its ability to solve complex issues.  

  • Prolog

Prolog introduces you to a separate world of its own, completely designed by logic. The abbreviation for Programming In Logic, Prolog has its unusual way of approaching an AI solution. Prolog requires three important factors from your side, rules, facts, and the desired result. Once you provide all these requirements, the programming language will figure out the link between the three and design an AI solution. 

Indeed, it’s a unique way of designing an AI-powered device, but it is flexible and surprisingly, powerful. The efficiency of this programming language is pretty high when it comes to backtracking and data structuring. 

  • C++

One of the major advantages of having C++ as your AI programming language is processing speed. When you consider AI processes, you talk about complex automated solutions to run efficiently. And, C++ won’t disappoint you in that respect. However, C++ is not a preferred language for leading Companies in AI. The reason behind that is the complex syntax and limited range of libraries. 

This is where C++ has another important feature to attract a wide range of companies, its cost-efficiency. C++ will provide a cost-efficient AI solution to fit your requirements when compared to other AI programming languages. Other than that, we can use C++ for OpenCV, which is one of the widely used open source libraries of computer vision.   

  • JavaScript

When it comes to versatility, JavaScript will definitely arrive ahead of Java. With continuous developments, multiple domain growth, backend use, ease of use, efficiency, etc, supporting the above statement. Apart from that, a widely used framework for deep learning, TenserFlow, finds home with JavaScript. Though JS lacks the popularity as gained by Java, the stability is certainly working in its favor. 

  • Java

JAVA is probably the most-used language around the globe for different processes and AI is definitely one of them. The best benefit of using the JAVA programming language is the presence of Virtual Machine Technology. What does JVM do? Well, Java Virtual Machine eases the implementation process, which saves your time and energy to compile the program again and again.

All you need to do is write the program and compile it on one platform, and the program is ready to be implemented on others. A huge disadvantage of using JAVA for AI processes is the processing speed, which is much lower than others.  

  • Haskell

One of the safest programming languages used for AI processes, Haskell has no room for errors. The programming language is well-known for resolving errors, during the compilation process and even before that. The features like build-in memory and code reusability increase the time allotted for planning the process. One aspect where Haskell finds itself behind other best programming languages for Artificial Intelligence projects is a small community. 

Haskell is not used by many programmers, so it’s still undiscovered and yet to expand its wings.

  • Julia

Do you want to talk in numbers? Julia will suit your requirement! The programming language is well-known for numerical analysis. The best feature of Julia is the dynamic type system, which allows you to use the language for literally any process. Other features involve in-built package manager, macro programming abilities, multiple dispatch support, and suitability with C functions. 

Again, the reason remains the same for its less popularity, unavailability of a huge crowd behind it. Julia has a to offer, you simply need to unveil the programming language. 

Ending Note

All the languages discussed above are the best programming languages for Artificial Intelligence projects. It’s just the choice of a project that suits your requirement the best. With a basic understanding of the project, you can simply choose the most suitable language and enhance the productivity of your company. 

After a lot of research, we have mentioned these data that will help you to engage in Artificial Intelligence projects. These languages have been given much importance and vary the development as per the needs and requirements. As a person or a business owner, you will face multiple challenges and to overcome, an AI and ML Consultant is must for those issues.

If you are looking for AI and ML Consulting services, then Ksolves works as one of the guaranteed perfection who works on generating the best results. So, you are just a call away in accomplishing the projects in a feasible manner.

Contact Us for any Query

Email : sales@ksolves.com

Call : +91 8130704295

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Shilpa Shrivastava
AUTHOR

3 thoughts on “Top 8 Programming Languages For Artificial Intelligence Projects

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Frequently Asked Questions

Which language among them is best suited For Artificial Intelligence as Beginner?

Python is widely considered the best language for AI projects due to its simplicity, extensive libraries, and strong community support. Other popular languages for AI include R, Java, and C++. However, Python’s versatility and rich ecosystem make it the preferred choice for most AI applications.

How Utilization of Java is done in AI projects?

Java is commonly used in AI projects for developing large-scale enterprise applications, natural language processing (NLP), and building AI frameworks. It is known for its performance and scalability.