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Top 7 Programming Languages For AI

Al ( Artificial Intelligence)  is one of the most crucial topics that IT industry is hovering around these days. The necessity and importance of Al ( Artificial Intelligence)  are great because it has the ability to help solve extremely difficult issues in different industries, such as education, health, commerce, transport, and utilities. Let’s through this article discuss and tackle Top 7 Programming Languages For AI.

Top 7 Programming Languages For AI


Java can also be considered a good choice for AI development. Artificial intelligence has a lot to do with search algorithms, artificial neural networks, and genetic programming. Java provides many benefits: easy use, debugging ease, package services, simplified work with large-scale projects, the graphical representation of data and better user interaction. It also has the incorporation of Swing and SWT. These tools make graphics and interfaces look appealing and sophisticated.


Lisp, being the second oldest programming language in the world, still holds a top position in AI creating due to its unique features. For example, Lisp has a special macro system which makes possible to develop a domain-specific level of abstraction and build the next level on it. Lisp in artificial intelligence development is known for its unique flexibility as it adapts to the problem you need to solve. Developers opt for Lisp in machine learning and inductive logic projects.


Python is focused on DRY (don’t repeat yourself) and RAD (rapid application development). Developed in the early 1990s, Python has become one of the fastest growing programming languages because of scalability, adaptability, and ease of learning. Python has hundreds of libraries that make any type of project possible, whether it is a mobile app, web app, data science or artificial intelligence. In Python, almost all idea can be quickly validated via 30-40 lines of code.

4- R

R is one of the most effective languages and environments for analyzing and manipulating the data for statistical purposes. Using R, we can easily produce a well-designed publication-quality plot, including mathematical symbols and formulae where needed. Apart from being a general purpose language, R has numerous packages like RODBC, Gmodels, Class, and Tm which are used in the field of machine learning. It has great importance in this field.


The name of Prolog speaks for itself; it’s one of the oldest logic programming languages. If we compare it with other languages, we can see it is declarative. It means that the logic of any program will be represented by rules and facts. Prolog programming for artificial intelligence can create expert systems and solving logic problems. Some scholars claim that an average AI developer is bilingual – they code both Lisp and Prolog.


C++ is faster than other languages. Its ability to communicate at the hardware level allows you to improve code execution time. It is extremely useful for artificial intelligence projects that are time sensitive. It can be used for statistical AI approach like those found in neural networks. C++ makes itself a good candidate for AI programs. In fact, a vast portion of machine learning and deep learning libraries are written in C/C++.


Haskell is named after Haskell Brooks Curry, an American mathematician, and logician. Haskell has three programming languages named after him: Haskell, Brooks, and Curry. Haskell is a purely functional programming language that can boast about its lazy evaluation and type interface features. Haskell the language is built around functions, useful blocks of code that do specific tasks. They are called and used only when needed.