Top 7 Best Programming Languages For Artificial Intelligence (AI) 2024

Because of the many advantages it offers and the ease and simplicity it has improved our life, artificial intelligence has now become a vital component of our everyday existence. The remarkable productivity and quality-of-life enhancements of AI programming benefit users worldwide. Even while they make news, search engines and smart speakers are but a small portion of the extensive AI technology now in use.

The term artificial intelligence (AI) basically refers to the machine-based imitation of intelligence human thought processes. To put it another way, artificial intelligence (AI) is a system that gathers and analyses vast volumes of data using programming techniques.

When it comes to helping businesses expand and reach their full potential, artificial intelligence has advanced significantly in recent years. These developments would not have been achieved without significant improvements in the programming languages that form the basis of artificial intelligence.

These days, as artificial intelligence (AI) has become more prevalent, so has the need for competent and effective programmers and engineers. Even though there are several programming languages available to help you get started with AI creation, no one programming language can be your one-stop shop for AI programming because different projects have different goals that require different approaches. It may therefore be challenging for those who are interested in the field of AI development to decide which programming language is best to learn and utilise.

This post will discuss a few programming languages you can learn that are connected to artificial intelligence. Let's examine what AI development means first, though.

What Is AI Development?

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Within computer science, artificial intelligence studies intelligent systems and technologies. By enabling computers to learn from experience and solve problems creatively, artificial intelligence programming aims to build machines that can think and act like people.

Artificial intelligence (AI) software is used for a range of applications that mimic human behaviour, such as language translation and problem-solving. AI programming allows robots to perform activities that ordinarily need human intelligence.

Roles of AI Development

Our lives are greatly impacted by artificial intelligence (AI), which is present in everything from personalised shopping to driverless cars. Among these positions are those in which medical professionals employ AI to forecast diagnosis, prognosis, and treatment results.

AI is used in banking to detect fraud, and in the military and defence sector to forecast cyberattacks and other national security threats.

Top 7 Best AI Programming Languages To Learn in 2024

• Python
• C++
• Java
• Lisp
• Prolog
• R
• Haskell

1. Python

At the moment, Python is considered to be the mother of all other languages. Python is perhaps the most well-liked and productive programming language for creating applications related to NLP and AI/ML. Additionally, it is perfect for deep learning and platform-neutral programming.

Because Python is a powerful programming language and its code is clear, succinct, and intelligible, coding becomes more pleasurable. With the aid of a big library, hundreds of AI/ML algorithms can be executed.

Python has a very easy syntax, so even if you are not experienced with AI programming, you may use it for Machine Learning processes. In spite of its effectiveness in a number of other domains, like website development and DevOps script writing, Python has excelled in AI/ML, according to a Forbes article.

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For developing custom artificial intelligence, Python is the preferred language due to its ready-to-use libraries (such TensorFlow, SciKit-Learn, and others), support for object-oriented programming, faster development times, and ability to test algorithms without actually running them.

The best thing is that Python's adaptability may be further increased by combining it with other languages, like Java. More than half of all developers choose Python for AI development since it is useful for web programming, soft computing, and ethical hacking. Thus, one of the greatest programming languages to master for AI is Python.

 2. C++

 Neural networks may be created using this computer language, which is an extension of the C programming language. The biggest benefit of C++ is its speed because AI development necessitates complex computations, which this language can expedite. It works well with statistical AI techniques like neural networks and is perfect for artificial intelligence projects with a tight timeline.
It can execute applications that are resource-intensive, performance-critical, etc., and it features a low-level memory control feature.

Compared to competing languages like Java, C++ is less expensive despite having a sophisticated syntax. Programming languages like C++ can be used in artificial intelligence (AI) for search engine optimisation and ranking.

3. Java

With an abundance of open-source packages, Java is a well-liked programming language. Java is an ideal choice for AI development since it offers an autonomous platform and is very user-friendly.

This programming language is standard and adaptable, enabling graphical data presentation, scalability, and faster debugging of code for huge organisations. Because of its Virtual Machine Technology, AI languages may be developed on a range of platforms and Java is an easy language to learn and adapt to.

4. Lisp

 In 1958, John McCarthy invented list processing, or LISP. Artificial intelligence can be developed using this programming language. Because of its flexibility and adaptability, LISP is perfect for machine learning. LISP is renowned for its dynamic object creation and rapid prototyping. However, LISP is no longer frequently used because the codes are harder to understand and it lacks good libraries.

Lisp has several qualities that make it a top choice for AI, including:

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a. Quick prototyping

b. Creation of Dynamic Objects

c. Collection of Garbage

d. Adaptability

5. Prolog

 Among the earliest programming languages is Prologue, often known as logical programming. It is an effective structure that relies on three components: objectives, regulations, and facts. 

Each of the three components needs to be defined before Prologue establishes connections between them to analyse rules and facts and reach a particular conclusion.

Because algorithms are implemented through logical searches and inferences, this language is perfect for building artificial intelligence systems since the solutions are logical and do not depend on pre-existing statements. Prologue is the best language to use when creating voice assistants, chatbots, and GUIs (Graphical User Interface).

Benefits of Using Prolog for AI

a. It makes use of an adaptable and strong framework for natural language processing, non-numerical programming, theorem proving, and AI in general.

b. It is a declarative language of formal logic. AI developers appreciate its pre-built search engine, nondeterminism, backtracking mechanism, recursive structure, high-level abstraction, and pattern matching.

6. R

 R is a scientific and statistical computer programming language that is free and open-source. For the creation of interactive graphics and other intricate visualisations, the R programming language is helpful. A broad variety of data processing tasks, from straightforward linear regressions to intricate three-dimensional simulations, can be handled by its design. 

R is an open-source programming language.R was developed as a programming language to handle various tasks such as machine learning and statistical computation. R has a wide user base, memory-efficient non-stop processing, object-oriented programming, strong extensibility, and is frequently used for forecasting.

Features of R that make it a good fit for AI programming among developers include:

a. The fundamental capacity of R to handle big data sets puts it ahead of Python's somewhat rudimentary NumPy module.

b. R can be used to work on many programming paradigms, such as object-oriented programming, functional programming, and vectorial computation.

c. User-created packages can extend R's functionality by adding various statistical techniques, tools, graphical devices, and import/export capabilities, among other things. This encourages language's growth and increases its appeal to data scientists and analysts.

 Because of its integrated data modelling and graphical capabilities, programmers can develop significant deep learning models more quickly and easily.

7. Haskell

 This programming language is entirely functional, meaning that every expression is assessed to produce a single value. Because Haskell does not have variables, it is mostly dependent on recursion when writing code. However, Haskell does have some mutable types, including lists and arrays.

Because of this, Haskell is ideal for developing complex algorithms that have several stages that culminate in a conclusion. Because the syntax arranges the code in lines with semicolons at the end of each line rather than indentation, it can be perplexing at first.

One of the best things about Haskell is its type system. It lacks a null value, therefore you cannot store anything in a variable or pass in nothing as an argument.

The economy of the future is fundamentally dependent on artificial intelligence. The foundation of AI development projects are programming languages, which enable software engineers to create innovative AI solutions without needing to learn the extremely specialised language that scientists use to interact with one another. For people who are interested in learning more about artificial intelligence, it may be helpful to study and comprehend these programming languages.