Top 10 Programming Languages for AI Development

Jan 14, 2022

Artificial Intelligence offers various benefits and delivers across hundreds of various use cases and situations, not to mention how simple and easy it has made things for us and has become part of our lives. AI has gone a long way in recent years to assist businesses in growing and realizing their full potential. These developments in AI would not have been possible without fundamental improvements in the programming languages that underpin them. 

The availability of dedicated and skilled developers and engineers increased as AI became more popular, as did the variety of programming languages accessible. While there are several programming languages to get you started with AI development, no single programming language is a one-size-fits-all answer, as different objectives necessitate a unique strategy for each project. 

Programming Languages

For AI development, a variety of programming languages are available. But how can you find the best option for you? Don’t worry, we’ve compiled a list of the top ten programming languages for AI development:

Java

Java is a user-friendly programming language that is simple to debug and run on any platform that supports Java. This means that if you switch systems, you won’t have to rewrite the code. 

It would be a fantastic choice for AI development because it creates high-quality visuals for AI graphics. 

There are also numerous AI libraries available, such as Neuroph, Deep Java Library, and others. 

Java has been utilized in a variety of applications over the years, including Android apps, server-side programming, and so on. As a result, all of its qualities, such as security and robustness, combined with architecture neutrality, make it an excellent choice for AI development. 

Python 

Python is the most widely used programming language for both web and AI development. 

It is a more complex language than other languages since it allows multiple programming paradigms, including object-oriented and procedure-oriented programming. 

It is no secret that Python is a basic, easy-to-use language that can be learned without any substantial commitment to comprehending its ideas. Python is easy to learn, but that doesn’t mean it’s lacking in functionality. This is an interpreted language with a short and easy-to-understand code. 

Its pre-built libraries, including MXNet, Pybrain, and NumPy, help to speed up the AI development process. All of these characteristics combine to make it the most popular programming language for AI development. 

Lisp

LISP deserves a lot of the credit for what we’re seeing from AI. It is the oldest AI-processing language, as well as the second-oldest language in general. With its expanded reach of converting thoughts into reality, LISP has traditionally been regarded as a tool for top AI businesses. The language sets itself apart from existing AI languages by focusing on precision. 

The use of the LISP language, on the other hand, is on the decline due to its numerous shortcomings. The language is well-known for its ability to perform miracles and is still utilized for logical answers, which qualifies it for inclusion on the list.

C++

Processing speed is one of the key benefits of using C++ as your AI development language. When it comes to AI processes, you’re talking about complex automated solutions that need to run smoothly. C++ will not let you down in this regard. 

C++, on the other hand, is not a preferred language for leading AI companies. The reason for this is due to the difficult syntax and limited library selection. Another essential element of C++ that attracts a wide range of businesses is its cost-effectiveness. 

When compared to other AI programming languages, C++ will deliver a cost-effective AI solution to meet your needs. Aside from that, we can use C++ for OpenCV, which is one of the most frequently used open-source computer vision libraries. 

JavaScript 

When it comes to flexibility, JavaScript will undoubtedly outperform Java. The above statement is supported by ongoing developments, various domain expansion, backend use, the convenience of use, efficiency, and other factors. Apart from that, TensorFlow, a popular deep learning framework, has found a home in JavaScript. Though JS may not have the same level of popularity as Java, its stability is a plus. 

R Programming Language

R is a popular programming language for artificial intelligence (AI) programs that deal with statistical analysis and computation. It is a robust and versatile language that comes with several packages, including RODBC, Models, and others. The best part about these packages is how simple it is to create machine learning algorithms. 

It’s a platform-agnostic language that can work with C++, Java, and other programming languages. Using the built-in tools for data modeling and visualization, R allows developers to design important deep learning models with minimal effort. If you want to do data analysis, general statistics, or visualization, you should use R without hesitation. 

Prolog

Prolog presents you to a world all its own, created only by logic. It is an acronym for Programming In Logic, and it has an innovative approach to AI solutions. It requires three key components from you: rules, data, and the desired outcome. Once you’ve provided all of these details, the programming language will work out how they’re related and create an AI solution. 

It’s a novel approach to creating an intelligence device, but it’s also adaptable and, shockingly, powerful. When it comes to retracing and data structuring, this programming language is quite efficient. 

Haskell

It’s a general-purpose and functional programming language with built-in modularity and laziness. This does not imply that this is a language for slacker programmers; rather, it implies that code is only evaluated when it is necessary. 

Pattern matching, lambda expression, types classes, type polymorphism, and list comprehension are among its characteristics. It has long been utilized for academic and research purposes. 

It is a versatile programming language with the ability to handle failures, which is presumably why it is regarded as a safe programming language. Because it allows libraries to develop efficient AI algorithms, Haskell is a great option for dealing with abstract mathematics. 

Scala

It is a new artificial intelligence programming language that is based on the JVM (Java virtual machine) environment. Even though it is new in comparison to other languages, it is seen to be appropriate for projects that require versatility. 

Its significant characteristics, including customizable interfaces, high-performance functions, and pattern matching, make it a preferable choice for AI development among programmers. Scala may be used to create highly competitive applications. Furthermore, this programming language is interoperable with Java and JavaScript, making coding faster and easier. 

Rust

Rust is a syntactically similar high-level general-purpose programming language to C++. It provides performance, speed, safe concurrency, and memory safety without the need for garbage collection, unlike C++. 

This multi-paradigm programming language has grown in popularity as digital companies such as Firefox, Dropbox, Discord, Yelp, and others have begun to use it. Because of its expressiveness and speed, while maintaining memory safety, it is frequently used in scientific computing and AI development.

All of the languages mentioned above are excellent choices for Artificial Intelligence projects. It’s simply a matter of selecting a project that best meets your needs. With a basic grasp of the project, you can easily select the most appropriate language and boost your company’s efficiency. 

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