What are the Best Programming Languages for Building AI Solutions?

Sector: Digital Product, Technology

Author: Nisarg Mehta

Date Published: 01/16/2018

What are the Best Programming Languages for Building AI Solutions

AI in itself is so strong and substantial that it has the capacity to convey yet another revolution in the field of Computers and 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 6009 AI startups have already been listed under AngelList.

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

AI is changing the business world by bringing many AI-based mobile applications into practice. However, the solution to artificial intelligence may seem complex to not just beginners but to the programmers working in this field for a long period as well. This complexity arises due to the lack of understanding as to which programming language will serve its 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 smooth progress in AI is 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 demands.

Top 5 programming languages for building AI solutions

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.

Best features of Python:

  1. Practical versions of libraries. (tensorflow, numpy, VTK, Simple AI)
  2. Open Source Libraries. (Numpy, Matplotlib)
  3. Great Framework. (scikit-learn)
  4. Effortless prototyping and building of apps.
  5. Easy to learn.
  6. Open Source.
  7. Modular programming.
  8. Fast testing.

2. Prolog

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

Best features of Prolog:

  1. Logic-based development.
  2. Expert system implementation.
  3. Easy rule implementation.
  4. Pattern matching.
  5. Supports backtracking.
  6. 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 vital.

Best features of Java:

  1. Strong Libraries. (Weka, Mahout)
  2. Easy usability.
  3. Scalability.
  4. In-built Garbage Collection.
  5. User interaction.
  6. Fast.

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++ has opted.

Best features of C++:

  1. Speed.
  2. Easy to learn.
  3. Real-world implementations.
  4. Genetic Algorithms
  5. Neural Network Implementations.
  6. Mission Critical Systems.

5. LISP

LISP (List Processing) is that high-level language that 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.

Best features of LISP:

  1. Supports Symbolic Programming.
  2. Garbage Collection
  3. Syntax Uniformity.
  4. Extensible.
  5. Rapid Prototyping.
  6. Machine Translations.
  7. A great prototyping tool.

Wrapping up

Artificial intelligence is here to stay. The sooner you realize this, the faster you could get hold of the market. No matter if you’re just starting out with AI development or starting a company that is into developing AI-based solutions for apps and IoT devices, you need to have a mastery over one or more of these programming languages to become a pioneer in the industry.

Get started today.

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