5 + 1 Most important programming languages used for AI Project Development

Introduction

A programming language is the backbone of any software to work properly. Especially when it comes to Artificial Intelligence, Machine learning, etc when you are expecting the machine to perform complex tasks as efficiently as a human, programming is one of the key aspects, to make the system robust and fully autonomous.

Another important factor is which programming language to choose to implement these features. There are several programming languages that exist in the world of computer science that has served various important roles. But When it comes specifically to artificial intelligence, Machine learning, Deep learning, Neural Network, Data Science, etc,  six languages out of a bunch are currently ruling the industry. Let’s talk about them one by one.

Python

Python is unquestionably one of the most important languages when it comes to Data Science, AI, and development in the related fields. Python was developed by a Netherlands based computer scientist, named Guido van Rossum, as a hobby in his free time.

Then it becomes a part of a project called “ Amoeba”. From there it started getting popular and in 1991 the first unofficial version was released. It is an object-oriented, Open Source programming language.

Python is very simple and readable. The syntax is very easy to learn. Even a highschool Kid can learn and implement Python in their projects. Python also supports a list of modules and packages, which makes it really useful to implement a solution for a variety of complex real-world problems. Some of the packages that are being used in the Software and AI industry is NumPy, TensorFlow, etc.

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But there some disadvantages of using Python. Python interpreter is comparatively slower than C, C++ compilers. 

Database connectivity using Python is not recommended and as good as other programming languages like JAVA.

Python is not good for mobile development projects.

R

R gained its popularity because of its extensive use in Statistical Analysis by researchers and Mathematicians. R is basically an implementation of S, which was developed by John Chambers, in 1996 in Bell Laboratory. Ross Ihaka and Robert Gentleman are the founders of R. This language was developed by these two gentlemen in Aukland, Newzealand. The initial version was developed in the year 1992 and the first stable beta version was released in 1995.

RODBC is the famous package associated with R. Also R has packages like G-model, readxl, vroom,readr. R is quite handy for data import, data modeling, data analysis, and related work.

JAVA

Java is one of the most popular programming languages in the world for the last 20 years. The widespread use of Java definitely makes it one of the best fit for AI programming.

Java is object-oriented, Portable, Once Written Read Anywhere Programming language. Java is also rich with ts libraries and packages which makes it quite handy for developers to work in  AI-related projects.

Some of the important packages JAVA uses in AI are 

1. Apache Jena: it’s an open-source java framework for semantic web and linked data application. 

2. Apache Open NLP: This framework is used for natural language processing in case of Machine Learning

3. Neuroph: Open source java framework for neural network creation

4. D3web: This framework is responsible for developing, testing, and applying knowledge to a given problem solution.

But Java is comparatively slower than C, C++ which means more response time.

LISP

Lisp was created by John McCarthy in the year 1958. Second oldest programming language next to Fortran. Lisp stands for list processing. Lisp is important for mathematical notation problem. Lisp supports programmers to write mathematical notations and expressions.

Lisp is a very powerful language. Lisp is very good for prototyping purposes. It’s symbolic programming. The use of Lisp was high in the 1970s and 1980s.

PROLOG

Prolog is one of the oldest languages in AI programming. The syntax is quite different than C++. This language supports pattern matching and automatic backtracking. Prolog was created in the year 1973, by Alain Colmerauer at the University of Aix-Marseille, France.

The programmer needs to specify rules, facts, and goals. Based on these three things prolog will try to find out the connection between them.

Pattern matching, database handling, and list processing are the main characteristics of Prolog.

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GOLANG

The last one which no one is not talking about is Go programming language developed by developers at GOOGLE. 

Golang was developed by Rob Pike, Robert Grismer, and Ken Thompson. Golang has the power to handle modern computational complexity.

Golang is enriched with libraries that can support applications for machine learning, deep learning, and TensorFlow apps. Golang is super awesome because of its concurrent model which makes applications pretty fast. Also, the syntax is pretty clean and simple, therefore easy to understand. Some programmers may argue whether go language is better than Python !! Golang is highly scalable and its concurrency model makes it a better choice for cloud computing.

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