According to PwC’s recent report, Artificial intelligence will boost the global GDP 14 percent (equivalent to $15.7 trillion) higher in 2030. No doubt, this makes it the most significant commercial opportunity in today’s economy. Besides, Artificial intelligence is the new horizon for application developers, which opens up a world of possibilities. Artificial intelligence, backed by machine learning and deep learning, helps produce better user profiles, recommendations, personalization, or incorporate smarter search. It also leverages a voice interface or intelligent assistance to improve an app. This also enables us to build human-like applications that can see, hear, and react.
So, if you want to become an Artificial intelligence application developer, which programming language should you learn to get an in-depth hold of AI? Of course, you need a programming language with many useful machine learning and deep learning libraries. Besides, it should have a feature of excellent runtime performance, enough tools support, a large community of programmers, along with a healthy ecosystem of supporting packages. No doubt, these are pretty much a good amount! However, we have 5 such programming languages for Artificial intelligence in place, which we will discuss in this blog.
1. Python
When it comes to the best programming languages for AI, Python leads the other equivalent AI programming languages with plenty of library support and a robust community. Some of its pre-built libraries like NumPy, Pandas, Pybrain, and SciPy are very helpful for programming. Some of the other libraries useful for deep learning Apache MXNet, PyTorch, and TensorFlow, whereas, for ML, you can use scikit-learn. Python is also a leading language for Natural Language Processing (NLP), and some of its NLP supported libraries are NLKT or SpaCy.
However, the learning curve for Python is very steep, although the development time is short compared to C++.
2. R
R language is the best programming language for machine learning for its data manipulation and analysis. Using R, one can produce a well-designed publication-quality plot, which includes mathematical symbols and formulae as needed. Apart from this, R has numerous packages like RODBC, Class, Gmodels, and Tm, used for machine learning. Using these packages, the implementation of machine learning algorithms becomes easy. This, in turn, helps to crack the business-related problems in Artificial intelligence.
3. Lisp
Lisp is a practical mathematical notation for computer programs. Lisp offers rapid prototyping capabilities. Thus, Lisp is ideal for projects which have a higher requirement of ML. Not only prototyping capability but also Lisp supports symbolic expressions, collection libraries, flexibility, etc. Also, Lisp allows the easy dynamic creation of new objects which leverage garbage collection. This is one of the reasons for its popularity among Artificial intelligence developers. Another vital feature of Lisp is it supports automatic garbage collection and interactive evaluation of expressions and recompilation of functions or files concurrently.
4. Prolog
Apart from Lisp, Prolog is one of the programming languages explicitly designed for Artificial intelligence development. Some of its unique features make it an ideal language to be used for machine learning. One of its outstanding features is pattern matching. The language is also characterized by automatic backtracking. All these features are applied in various aspects of Artificial intelligence development. Prolog is also backed by quite many frameworks, which make programming much more straightforward. Apart from the AI projects, Prolog is also used in building medical systems
5. SmallTalk
Smalltalk is an object-oriented and also a dynamically typed programming language that can be used for machine learning and artificial intelligence. It is not a new language and has been in existence since 1970. This is a language meant to meet the goal of human-computer interaction.
Among the object-oriented languages, Smalltalk implements complex tasks in a more natural and organized way. Besides, it supports rapid and iterative programming, the more natural development of GUI, and prototypes. Alongside, if you want to design the user interface following the MVC patterns, SmallTalk supports that too to produce an effective GUI.
Final words:
As we see, each of the languages mentioned above has its own beauty with compatibility with Artificial intelligence. However, it isn’t easy to pick any one language as the best programming language. Moreover, the list here is limited to only 5. There are many other equally efficient languages like C++, Java, Haskell, Julia, etc., which are excellent for developing artificial intelligence. So, finally, it really comes down to your choice and the unique demands of the project to pick the suitable programming language.