5 Most Popular AI Programming Languages

5 Most Popular AI Programming Languages

Artificial intelligence, also known as AI Programming, is the hot technology right now and it is one that will only further permeate all aspects of our lives. Though AI is not new, there has been a recent expansion in machine learning and AI technologies.

The fullest potential of AI is not yet known, even by the most technologically advanced thought leaders. And, that is why now is the time to get informed, learn about new technology, and acquire the skills necessary to program for such complex projects.

For software developers, this is particularly true and a reality that should not just be accepted but anticipated with education and training.

To be best prepared for the growth of IoT and that further fuels the growth of AI, programmers may need to learn new programming languages if they want to be ready and proficient in ideal artificial intelligence programming languages.

  • Java

Java can also be considered as 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, graphical representation of data and better user interaction. It also has the incorporation of Swing and SWT (the Standard Widget Toolkit). These tools make graphics and interfaces look appealing and sophisticated.

  • Prolog

This language stays alongside Lisp when we talk about development in AI field. The features provided by it include efficient pattern matching, tree-based data structuring, and automatic backtracking. All these features provide a surprisingly powerful and flexible programming framework. Prolog is widely used for working on medical projects and also for designing expert AI systems.

  • Lisp

Lisp is one of the oldest and the most suited languages for the development of AI. It was invented by John McCarthy, the father of Artificial Intelligence in 1958. It has the capability of processing symbolic information effectively.

Its development cycle allows interactive evaluation of expressions and recompilation of functions or files while the program is still running. Over the years, due to advancement, many of these features have migrated into many other languages thereby affecting the uniqueness of Lisp.

  • Python

Python is considered to be in the first place in the list of all AI development languages due to simplicity. The syntaxes belonging to python are very simple and can be easily learned.

Therefore, many AI algorithms can be easily implemented in it.

Python takes short development time in comparison to other languages like Java, C++ or Ruby. Python supports object-oriented, functional as well as procedure-oriented styles of programming. There are plenty of libraries in python, which make our tasks easier.

For example: Numpy is a library for python that helps us to solve many scientific computations. Also, we have Pybrain, which is for using machine learning in Python.

  • R

R is one of the most effective language and environment 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. These packages make the implementation of machine learning algorithms easy, for cracking the business associated problems.

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