The Best AI Programming Languages

As artificial intelligence continues transforming the reality of all economic and technological areas worldwide, companies seek to incorporate it into all processes to accelerate growth. With AI, businesses can save time and money by automating and optimizing routine processes.

But to implement artificial intelligence, it's necessary to have software developers who are up to the task. One of the main requirements is knowing the best AI programming languages to provide a company with a service that meets its objectives.

If you're a software developer or just starting, it's important to know the top 10 programming languages. But let's start at the beginning:

What are AI Programming Languages?

AI programming languages are tools used to create applications that simulate human intelligence. These languages make it possible to create algorithms capable of learning from data and making decisions. Each language works differently and has its peculiarities, so it is essential to choose one that simplifies coding and offers libraries adapted to tasks such as machine learning and data analysis.

The 10 Best AI Programming Languages

Not much has changed over time. The leaders in the top spots remain on their podiums. Here are the 10 best AI languages of 2024:

1. Python

At the top is Python. Its easy-to-use syntax and rich ecosystem of libraries make it the language of choice for developers. Python is the most popular and easy-to-use programming language in the AI field, thanks to its origin as a powerful data analysis tool.

2. Java

Java is commonly used to develop sophisticated software applications. It's known for its ability to build adaptable systems compatible with various computing platforms and to integrate with AI libraries to implement machine learning algorithms. Java is important for AI, particularly due to its prevalence in mobile app development.

3.C++

Known for its powerful processing capabilities, C++ excels in handling AI tasks that require high computational power and precision in hardware resource management. Its versatility, performance, and low-level capabilities facilitate smooth communication between software and hardware components. Although C++ might not be the first choice for developers, it's worth noting that many deep learning and machine learning libraries are written in C++.

4. Lisp

Lisp stands out with its high-level functional programming, perfectly tuned for AI development. It's used for symbolic reasoning tasks because it can manipulate symbols and data structures. Lisp has been around since the 1960s and has been widely used in scientific research in fields such as natural languages, theorem proving, and artificial intelligence problem-solving. Although Lisp is the second oldest programming language still in use, it includes several features that are fundamental for successful AI projects.

5. R

R might not be the perfect language for AI, but it's fantastic for processing very large numbers, making it better than Python on a large scale. Designed for statistical computing and data analysis, R has a wide variety of visualization libraries, making it a favorite among those who like to find hidden stories in data.

6. Julia

Julia is one of the newest languages on the list, created to focus on performance computing in scientific and technical fields. It stands out for its high performance and fast prototyping. Julia offers fast processing speed and the ability to perform complex calculations, making it ideal for sectors requiring thorough data analysis. Additionally, it features an easy-to-use syntax similar to Python's.

7. JavaScript

JavaScript is used to develop applications like chatbots and recommendations and for rapid prototyping. This programming language creates interactive AI functions in web browsers, such as chatbots, and quickly prototypes AI ideas with libraries like TensorFlow.js. Developers use JavaScript to integrate AI into web interfaces, from AI-driven visualizations to real-time user interaction.

8. Scala

Scala is a friendly and reliable language, a good choice for building machine learning algorithms and extracting information from large data sets, as well as managing complex content in general. It combines functional and object-oriented programming to create high-performance applications in the AI field. It's a language where clarity meets efficiency.

9. Haskell

Based on the functional programming paradigm, Haskell offers a set of principles conducive to processing complex data structures in AI development. On one hand, it allows developers to describe algorithms explicitly while providing type safety and seamless multicore parallelism.

10. Prolog

Easy pattern matching and list manipulation are standout features of Prolog, which means "programming in logic." These features make the logical language a good choice for AI. Prolog is ideal in cases where developers need to focus on problems because the language can execute the program using its search tools.

How to Learn AI Programming Languages

To start in AI, you'll need to master key skills such as basic math and statistics, which are essential for understanding AI operations and algorithms. Additionally, programming knowledge is essential due to its simplicity and the wide range of available AI resources. Data manipulation skills and an understanding of data structures are integral to implementing AI solutions.

Continuously updating these skills through practical projects and learning programs can develop your AI expertise and keep it current so that you never fall behind—something you can't afford if you work in technology. Furthermore, knowledge of the best AI tools will provide significant benefits when creating your code, such as saving time and reducing costs.

There are many languages to choose from. However, when learning, it's advisable to choose those that offer the most benefit with the least effort. The AI programming languages on this list will help you achieve that goal. Delving into the world of programming languages is infinite and fascinating. Our advice when choosing the right one? Go for the one that meets your needs and feels most comfortable to execute.