Artificial intelligence has now become an important part of our businesses and daily lives. It offers innovative solutions to business problems in the form of hundreds of unique use cases, thus making lives easier.
Over the years, AI has been assisting businesses to grow and unlock their true potential. The global artificial intelligence market is expected to reach $267 billion by 2027. AI has brought technology to a whole new level and paved the way for innovation for global industries. Whether it’s healthcare or eCommerce, the benefits of AI development are twofold.
Having said that, core AI programming languages are facilitating the development of artificial intelligence in the most promising directions. The software development industry is constantly evolving. Therefore the need for developers with knowledge of AI programming is fluctuating too.
Some of the most common programming languages for AI and machine learning are available to get you started with AI development.
But the question still stands, what is the best programming language of them all? Choosing between multiple programming languages for AI can be overwhelming. Plus companies and/or developers should expand their horizons by experimenting with not just one, but with various AI programming languages to open up more doors of opportunities.
In this blog, I will discuss some of the most popular and best programming languages for AI development moving forward in 2022. While there are several AI programming languages out there some are new and some old, but all equally important to get you started with.
So let’s jump in!
Python is currently the best language for research and development in machine learning with great community support. Don’t just take out words for it. According to google trends, for the past 5 years, interest in Python language among developers has spiked, when compared to other languages such as java, scala, R, prolog, Julia, etc.
Even though python is the best language for machine learning techniques, the question is why? This language involves less code and is easy to use. The syntax of python is very simple. Meaning if you have basic knowledge of one programming language learning python becomes easier.
This simplicity makes the entire coding and execution process much faster. So, if you want to get started with AI programming for beginners, then Python is the most suitable one.
Moreover, python is a popular programming language that is known for having a large number of free libraries, which not only saves time but effort too, in the entire development cycle. Python grew by 18.5% in the last 5 years. Thus making it one of the most favored languages.
Additionally, it is efficient, reliable, and used for a variety of mobile and desktop applications, web development, hardware programming, and more.
Who doesn’t know about C++? It is one of the most popular and general-purpose programming languages in use today. Speaking of AI this programming language is exceedingly used in game development, robot locomotion, and network security.
If you are on a time crunch, C++ is the right choice for your project because it is known to accelerate the development process. Not only this, it enables faster implementation along with quick response time. It’s because of these unmatched features that half of the developer community pertaining to artificial intelligence prefer C++ to successfully execute related projects.
Most importantly, it is less expensive as compared to other AI programming languages such as Java. Some of the most common advantages of C++ are and are not limited to:
Java was created by a Canadian computer scientist in the early 90s, James Gosling. It’s been 20 years since its inception and this AI programming language is still going strong. Java is the most powerful programming language because just like Python, it has a rich library.
Moreover, Java is user-friendly, easy to learn, flexible, and quite versatile, among other things. It is machine-independent with debugging convenience and scalability.
Speaking of which, application scaling is very important when it comes to choosing programming languages for AI development. Scaling offers high cross-functionality and portability for the programs written once to run across multiple platforms such as desktops, mobiles, embedded systems et al.
Many IT companies around the world are already working with Java to develop infrastructures, software, applications to simplify integration and reduce compatibility issues. Along with Python, Java was one of the top five most widely used programming languages around the globe, in 2020.
This open-source programming language for AI development is quite popular among the data scientist, data miners, and statistician community, and is developed by Ross Ihaka and Robert Gentleman for data analysis.
Where python is about general-purpose programming, R is more inclined towards statistical computing. It is more suitable for developing statistical software. Companies like Uber, Airbnb, etc. use R. for statistical analysis.
R is super compatible with multiple operating systems and it offers sophisticated graphic systems for statistical visualization such as graphing or plotting.
Moreover, it has a wide array of packages like dplyr, readr that can transform unstructured data into structured. It is highly compatible with other languages such as C, C++ (best programming language for games), Java, and Python.
Lik java, R is also a platform-independent language. On the downside, R lacks basic security due to which it can not be embedded into web applications. Plus, it is difficult to learn, unlike Python.
Now, if you prioritize functionality above everything else, then Julia is probably the right choice. Let’s see why? This programming language was specifically designed to cater to data mining, data science, and machine learning.
The main reason behind the introduction of this language was to address gaps in the python programming language. But the most important question that whether Julia is better than python or vice versa is still debatable.
Julia has an interactive command-line called Read Eval Print Loop aka REPL to support developers with quick commands and scripts.
Moreover, it offers fast performance due to the LLVM framework. Additionally, its syntax is super simple and straightforward which makes it easier to learn. Last but not least, Julia can easily support the use of external libraries.
It is one of the most flexible and powerful programming languages for AI development and Machine learning. Prolog is a logic programming language, which was developed by a French computer scientist named Alain Colmerauer in the 1970s.
Its most common features are efficient pattern matching, tree-based data structuring, and automatic backtracking. Prolog was specifically designed for natural language processing, which is why this technology is mostly used for developing chatbots.
It involves procedural programming with a focus on facts, rules, and queries. Since chatbots and virtual assistants are on the rise, we will see rather an extensive implementation of Prolog for AI in the future.
LISP stands for list processing, is considered as one of the oldest among artificial intelligence programming languages developed around 1960 at the Massachusetts Institute of Technology (MIT) by John McCarthy, and its dialect language common lisp was introduced in the 1980s.
Some say that advancements in AI would not have been possible if it wasn’t for LISP. Due to its usefulness, common LISP became the standard language for AI development.
It offers rapid prototyping along with dynamic object creation features and flexibility, because of which it is one of the best programming languages for machine learning and is favored by AI developers, to-date.
Therefore the adaptability to this AI programming language is limited by the lack of tools important for implementation.
This is my opinion on what’s next in AI programming. Learn about the AI programming language trends back in the year 2020 and make your own guess!