Top 10 Best Programming Languages for Artificial Intelligence

Getting started in Software testing

Everyone talks about Artificial Intelligence these days but what exactly are the languages required for AI?

AI (Artificial Intelligence): It is basically a branch of Computer Science which targets on producing smart machines which can work and act like humans. Some Interesting links :

How AI is implemented?

It is accomplished by studying the human neural brain network and it’s working after which certain use cases are developed. These use cases are then processed and the final output is recorded. Then the machine is developed on the basis of the recorded result.

Several fields such as computer science, biology, psychology, linguistics, mathematics contribute to AI. Over time AI has been dominant in several fields such as robotics, gaming, vision systems, speech recognition etc.

Top 10 Best Programming languages for Artificial Intelligence (AI)

1. Python: The simple and seamless nature of Python makes it one of the best languages to learn AI. Python is in the big boom nowadays and with lots of AI oriented libraries makes it, perfect language for AI.

  • Simple syntax.
  • Shorter development time compared to other languages.
  • Object-oriented as well as procedure-oriented approach.
  • Compatibility with a huge number of libraries.

2. C++: The biggest advantage of C++ is its speed. It is one of the fastest programming languages, as it provides quicker response and fast execution time.

  • Faster Execution time (Used in gaming and search engines).
  • Huge availability of several library functions and tools.
  • Real-world implementations and genetic algorithms since it is object-oriented.

3. Java: Java is “write once run anywhere language”. This is the biggest advantage of Java as the generation of the bytecode can run on any platform. Once the code is compiled we can run it on any machine.

  • Portability no need for recompilation once compiled.
  • Swing and Standard Widget Toolkit incorporated for graphical interfaces.
  • Inbuilt garbage collector.

4. LISP : Lisp stands 2nd in the list of oldest programming languages after FORTRAN. It’s flexibility for quick prototyping and experimentation has made it a standard AI language.

  • LISP is very fast and efficient in coding.
  • The concept of memory management, initially designed for LISP. Thus it facilitates a garbage collector.
  • Provides high level debugging and advanced object-oriented programming.

5. R Language: It is one of the most efficient languages when it comes to analyzing and manipulating statistical data.

  • Data analysis is very reliable.
  • Mathematical calculations to process the data.
  • Apply various statistical concepts.

6. Prolog: It stands for programming in logic. It consists of a small but well-built programming framework.

  • Based on logical programming and fully object-oriented.
  • Supports the backtracking mechanism.
  • Pattern matching
  • Automatic memory management.
  • Supports linkage with other programming languages such as C/C++.

7. Javascript: It is an object-based scripting language which was developed for performing coding on web-pages.

  • Security, JavaScript can’t access local files which keeps security and privacy not an issue while developing a project.
  • Its fast performance is a key point for its huge success.
  • It is quick to develop and debug.

8. Haskell: It is the purest functioning programming language developed. Functions are considered as values like integers and Strings.

  • Lazy evaluation allows the result of one function to be handed to the other function on the same line of code.
  • Haskell uses monads, a structure that functions like an assembly line where each stop on the line does a different job.
  • No side effects, code cannot affect the state of a computer which makes it less prone to errors.

9. Julia: It has been developed basically for scientific computing. High performance was the main aim.

  • Dynamic typing and fast performance
  • Shell-like capabilities for managing different processes.
  • Easy conversions and promotions for numeric and other data types.

10. NIAL: NIAL is an interactive programming language that has data-structure concepts similar to LISP. It is completely based on array theory and gives mathematical descriptions of the real world data objects.

  • Defines data types as nested rectangular arrays.
  • Good for prototyping.
Conclusion

According to your problem or requirements you can select appropriate language. — R Bhave

Python is the most recommended language if you are about to start learning Artificial Intelligence. With much needed build-in libraries like sklearn, pandas, numpy & matplotlib the data load is simplified. C++, Lisp & Java are also good options for A.I implementations. In fact, languages like Prolog & Julia are designed for specific scientific purposes. For manipulating statistical data, R programming is also an good option. The choice depends on your problem.

Abhishek Deshwal

A tech enthusiast always looking forward to explore new technologies and trying out the latest gadgets.

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