Businesses are in constant pursuit of enhanced Artificial Intelligence (AI) solutions to integrate into their systems. As per the International Data Corporation’s (IDC) report, the AI market is projected to have a Compound Annual Growth Rate (CAGR) of 17.5%, with an estimated revenue of $554.3 billion by 2024. This would result in a market value exceeding $500 billion. However, to create effective solutions, the first step is to select the most fitting programming languages for AI software.
In this article, we will outline the ten best programming languages for AI development in 2022.
Python is a flexible high-level programming language that is renowned for its use in Artificial Intelligence (AI), Machine Learning (ML), Data Science, Web Applications, Desktop Applications, Networking Applications, and Scientific Computing. Being one among the most widely used programming languages today, Python offers developers a multitude of features and capabilities to create applications for various purposes.
Python is well-equipped with specialist libraries such as Keras, Pytorch, Scikit-learn, MXNet, Pybrain, and TensorFlow, making it an ideal choice for AI projects.
In addition, Python is an ideal option for developing natural language processing (NLP) and artificial intelligence (AI) applications due to its powerful text processing capabilities, simple-to-understand syntax, and modular scripting approach.
Python is popular for its user-friendliness and accessibility, making it an excellent programming language for novices. The code is concise, readable and intuitive, making it easy for people to comprehend it and customize it to their specific requirements. Moreover, the Python community is vast and passionate, providing a wealth of valuable resources and a welcoming environment for collaborators, users, and enthusiasts.
Python is utilised by a myriad of companies, including Google, NASA, Amazon, Instagram, Reddit, JP Morgan Chase, Intel, IBM, Netflix, Facebook, Pinterest, and several others.
Top programming languages for AI development
Lisp (once designated as LISP) is a preferred programming language for artificial intelligence.
The programming language Lisp was created in 1958, and it was named after one of its earliest applications, ‘List Processing’. By 1962, Lisp had made substantial advancements, enabling it to handle complex Artificial Intelligence (AI) issues with ease. Hire remote Objective-C developers to work on Lisp-based AI projects.
Despite its complex syntax and high-cost libraries, Lisp remains a potent programming language for software development. It is well-suited for Artificial Intelligence (AI) projects, providing a variety of advantages unmatched by other languages. These advantages include the ability to rapidly create prototypes, precise garbage collection and memory management, and powerful macro capabilities for quick and flexible programming. Furthermore, Lisp has been widely used in AI research, enabling developers to build intricate algorithms and models effortlessly. Ultimately, Lisp is a reliable language that has proven to be an irreplaceable component in AI development.
- Rapid prototyping
- Generating dynamic objects
- Executing data structures as a program
- Modifying programs as data
- Necessitates garbage collection.
Java is an extensively used server-side programming language for artificial intelligence application development. It is well-known for its custom virtual machine, which makes it the preferred choice for cross-platform development. Additionally, Java is the preferred language for creating Android applications.
The popular messaging app Snapchat, face-modification application FaceApp, and widely used Google Lens are examples of Android applications that incorporate artificial intelligence technology and have been built with the Java programming language. In addition, Java provides numerous machine learning libraries that offer capabilities beyond those of mobile applications, including:
- Java Deep Learning Library
- Java-based Machine Learning Library
Top programming languages for developing artificial intelligence
C++ is a longstanding low-level programming language that is best suited for hardware and machine-oriented projects, but not for modern conceptual software development.
Given its capability for low-level programming, C++ is particularly well-suited for developing fundamental artificial intelligence (AI) models. For example, developers frequently utilize C++ to build neural networks from scratch and to translate user-generated programming into machine-readable code.
R is a highly popular programming language for artificial intelligence (AI) that is valued by both novice and advanced statisticians. Although it may not be the most appropriate language for AI development, it is exceptionally proficient at conducting complex calculations.
Artificial Intelligence (AI) and Machine Learning (ML) rely heavily on extensive data and its efficient analysis. Therefore, software developers often choose to use the programming language R to process and present this data in effective and meaningful ways. In the realm of statistics, R is often deemed to perform better than its competitor Python in accuracy and functionality.
Prologue is a declarative programming language that is extensively used in the fields of natural language processing (NLP) and computational linguistics. It is the preferred option for tasks like symbolic reasoning, database applications, language parsing, and natural language processing because of its ability to represent and reason about knowledge in an intuitive and efficient way. Prologue is renowned for its capacity to articulate and prove complex logical statements, making it a potent tool for problem-solving.
Although it is not widely used in commercial applications, Prologue is expected to experience a resurgence in 2022 owing to its significance in the development of expert systems, theorem proving, type systems, and automated planning.
Haskell possesses a number of advanced capabilities, including type classes that enable type-safe operator overloading.
Haskell is a programming language that has gained popularity in educational research due to its support for Lambda expressions, pattern matching, type classes, list comprehension, and type polymorphism. Additionally, Haskell is renowned as a secure programming language for Artificial Intelligence (AI) applications, providing exceptional adaptability and the capability to manage errors reliably.
Top programming languages for developing artificial intelligence
Wolfram enables its users to achieve fast and efficient processing speeds. Featuring over 6,000 internal functions devoted to symbolic computation, functional programming, and rule-based programming, Wolfram is an optimal resource for managing arbitrary data and structures.
Wolfram Language, a favoured computer algebraic system, is highly regarded for its ability to execute complex mathematical operations and vast natural language processing tasks. Its attributes have cemented its position as a top choice for individuals requiring support in solving challenging mathematical problems or conducting intricate natural language processing tasks.
Julia, a fairly recent programming language for artificial intelligence, is quickly gaining prominence as one of the leading languages in the field. Despite its relative youth, the Julia community is expanding rapidly, and its consistently high ranking is a testament to the language’s abilities and potential.
Julia’s reputation as a programming language is attributed to its user-friendly interface and robust data visualisation tools. Moreover, it is well-regarded for its efficient memory management, debugging features, and capacity for metaprogramming.
The Julia programming language offers direct support for C functions, a dynamic type system, and parallel and distributed computing capabilities. Furthermore, it provides several pre-made models, algorithmic assistance, and packages for probabilistic programming, including:
- MLJ.jl package
- Flux.jl package
- Works.jl package
Rust is a versatile programming language intended to provide significant abstraction. It has a syntax that closely resembles that of C++. Nevertheless, it is capable of ensuring memory safety without requiring garbage collection and supports optional reference counting.
Rust is a sophisticated programming language that has garnered extensive popularity in the AI development field due to its multitude of advantages. It delivers enhanced performance, speed, security, and concurrency, making it a prime option for the development of large-scale software. With its distinctive characteristics, Rust has become one of the most coveted languages for AI programming.
Rust is utilized by several popular companies which include Firefox, Dropbox, Yelp, npm, Cloudflare, Azure, Deno, Discord, and Polkadot.
Artificial Intelligence (AI) is no longer a passing fad, but it is progressively becoming omnipresent in diverse applications, ranging from autonomous vehicles to grammar correction. This pervasive use of AI has fostered a conducive environment for companies to discover novel opportunities to utilize AI in their operations.