Top 5 programming languages for building AI solutions. The

Top 5 programming languages for building AI

The topic that created much buzz in the world of computer
science last year is clearly “Artificial Intelligence”. Thanks to Mark
Zuckerberg for showing his deep interest in the development of Artificial
Intelligence and making it a trending topic of 2017.

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AI in itself is so strong and substantial that it has the
capacity to convoy yet another revolution in the field of Computers and of
human intelligence as well. This is the very reason that many geeks have
already begun working in the development of AI, for it is best to strike the
iron while it’s hot.

Around 1031 AI start ups have already been listed under
AngelList. According to Forbes, around 65% of investment made in the field of
AI has already been absorbed by leading companies based in U.S. In the year
2016 itself, a total of $39B was invested by companies in the AI market making
it a massive industry.

Solution to artificial intelligence may seem complex to not
just beginners but to the programmers working in this field since a long period
as well. This complexity arises due to the lack of understanding as to which
programming language will serve their purpose the best. There exist many
programming languages for the development of artificial intelligence but
choosing the best among them is what the trick is.

All it takes for the smooth progress in AI is an intelligent
decision making while opting for the right programming language as per one’s
individual business.

There is no single language that serves each and every
purpose hence, no language can be declared as best. How perfect any language is
for any individual depends on what he is looking forward to and what are his

Here are the top 5 programming languages for building AI

1.     Python

One of the leading languages used for
developing AI Projects is Python which is because of its simplicity and easy
coding behavior and is especially used in health related startups involving AI.
One of the primary reasons for using Python is because it is the collation of
both Java and Lisp hence; you potentially get to use the essential features of
the two. Another reason for Python’s popularity is the engagement of developers
because of its dynamic features.


features of Python:

Practical versions of libraries.
(tensorflow, numpy, VTK, Simple AI)

Open Source Libraries.
(Numpy, Matplotlib)

Great Framework.

Effortless prototyping and building of

Easy to learn.

Open Source.

Modular programming.

Fast testing.


2.     Prolog

The reason Prolog is preferred for AI
solutions is that it pretty much revolves around a dedicated set of mechanisms
which consists of a small, flexible yet well-built programming framework. Using
Prolog one can exploit basic but constructive features of LISP as well.


features of Prolog:

Logic-based development.

Expert system implementation.

Easy rule implementation.

Pattern matching.

Supports backtracking.

List handling mechanism.





3.     Java

Java is in the top five because of its
familiarity and easy to use features. This OOP language allows easy coding of
algorithms which covers the major part of AI. Java is always a choice of those
developers who plan to develop large scale projects and when portability is


features of Java:

Strong Libraries.
(Weka, Mahout)

Easy usability.


In-built Garbage Collection.

User interaction.



4.     C++

The very reason C++ is used in AI
solutions is its speed; it is probably the fastest language out of all.
Therefore, whenever speed is the prime concern of any AI developer, C++ is


features of C++:


Easy to learn.

Real world implementations.

Genetic Algorithms

Neural Network Implementations.

Mission Critical Systems.








5.     LISP

LISP (List Processing) is that high
level language which impresses AI developers quite well and has been used in
many classic AI Projects as well. The factor that places it at the last
position is that, in comparison to others it is not fast.


features of LISP:

Supports Symbolic Programming.

Garbage Collection

Syntax Uniformity.


Rapid Prototyping.

Machine Translations.

Great prototyping tool.



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