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    The world of information technology is rapidly changing. Whereas before, the scope of AI was limited mainly to scientific research and defense, today, for many applications, having a suitable AI solution may become the only way to ensure their competitive advantage and place in the market. In other words, implementing artificial intelligence systems in the next decade is a given and a big challenge for existing enterprises.

    Of course, it is crucial to use the full power of artificial intelligence in the interests of your business on time. However, it is equally important to have specialists competent in this field at your disposal who can create practical and reliable AI models.

    So, it’s time to explore the most popular programming languages for AI development to understand the skills developers must demonstrate when hiring. And make sure to check out our portfolio, where you can see examples of applications our team developed based on AI and ML technologies.

    portfolio of Academy Smart
    Projects Academy Smart has delivered

    TOP-6 best programming languages for AI

    Artificial intelligence is a branch of computer science and engineering that focuses on creating intelligent machines that can perform tasks that typically require human intelligence, such as learning, problem solving, perception, and decision-making. The concept of AI has been around for centuries, but the actual development of AI as a scientific field began in the mid-20th century.

    Fortran was the first programming language for AI development, but the LISP and Prolog contributed the most significantly.

    LISP, “LISt Processing,” was developed in the late 1950s and became a popular language for AI research in the 1960s and 1970s. LISP’s primary data structure is the linked list, which is well-suited for AI tasks such as natural language processing and symbolic reasoning. LISP is also known for its support for functional programming, which emphasizes using mathematical functions to transform data.

    Prolog, which stands for “PROgramming in LOGic,” was developed in the 1970s and is based on first-order logic. Prolog’s syntax and semantics are designed to enable the declarative representation and manipulation of knowledge. Prolog has been used for expert systems, natural language understanding, and automated theorem proving.

    LISP and Prolog continue to be used in AI research and development today. However, more modern languages, such as Python and Java, have given their dominant popularity to AI apps in recent years.

    What branches of AI technology may be helpful for your business applications?

    They often overlap and draw from each other to create more advanced AI systems and perform many functions, improving operations, reducing costs, and increasing revenue.

    AI technology can be beneficial in many ways. Here are a few examples:

    To create a perfect AI application, you must systematically combine knowledge of algorithms, programming languages, and domain-specific expertise to solve complex problems. For AI design, developers often require additional software tools, among which R and Matlab stand out. They have a wide range of built-in functions and libraries for statistics, linear algebra, optimization, and other mathematical operations that are commonly used in AI development.

    Unsurprisingly, the demand for talented AI programmers constantly grows, and finding them independently in practice isn’t easy. In the article on recruiting IT professionals, you will find valuable tips on making this task easier for yourself. And now, let’s look at the best programming languages ​​in the field of AI today.

    1. Python

    Python is AI developers’ most prevalent programming language due to its syntactic simplicity and versatility. It is widely used because it is less complex than C++ and Java and supports object-oriented, procedural, and functional programming styles. Python is a portable language used on various platforms such as Linux, Windows, Mac OS, and UNIX.

    Python’s features, such as interactivity, interpretability, modularity, and dynamic, portable, and high-level programming, make it unique. Python supports the development of neural networks and NLP solutions with its simple function library and more user-friendly structure. Additionally, it supports the testing of algorithms without needing to apply them.

    Python programs are slower than C++ or Java examples because of an interpreter with slower compilation and execution, but they take much less time to develop. Its programs are typically 3-5 times shorter than equivalent Java or C++ programs, thanks to Python’s built-in high-level data types and dynamic typing. Python’s powerful polymorphic list and dictionary type, for which rich syntactic support is built into the language, finds use in almost every Python program.

    Python is a highly efficient programming language used for developing AI applications, offering several advantages over other programming languages. One of the most significant benefits is its simple syntax, making it easier to test and focus on programming itself. Additionally, Python is equipped with built-in libraries, providing a streamlined approach to development. That allows developers to focus on building AI applications rather than worrying about the underlying structure.

    Python offers a variety of handy tools that make this language the best choice for AI programming:

    Thus, due to its simple syntax and compact code, Python is one of the best programming languages for developing AI applications which offers several advantages, including:

    2. Java

    Java is a multi-paradigm programming language that adheres to object-oriented designing and the “Written Once, Run Anywhere” principle, making it an ideal language for developing artificial intelligence applications. It can run on any platform without the need for recompilation. Java is particularly suited for NLP and search algorithms and can run neural networks. While Java’s syntax is similar to C and C++, it is easier to use and includes an automatic memory manager to simplify the work of developers. Even if Java programs are slower than C++, they have significantly more performance than Python.

    Java offers several built-in tools and libraries that make it suitable for AI programming, including:

    So, platform independence, high efficiency, and the large community of Java engineers make this language one of the most popular and in demand in AI application programming.

    3. C++

    C++ is a high-performance programming language that prioritizes speed, making it an excellent choice for developers who value efficiency. Fast execution and quick loading time suits applications such as search engines and computer games well. With C++, developers can leverage various algorithms and statistical methods for artificial intelligence. The language also supports program reuse through inheritance and data hiding, significantly saving time and cost.

    C++ is a multi-paradigm program that supports object-oriented principles, which help organize data. Its rich library functions and software tools make it highly versatile. C++ is particularly well-suited for machine learning and neural networks, making it an ideal tool for tackling complex AI problems.

    However, C++ has limitations when it comes to multitasking, and it is only suitable for using the kernel or database of specific systems or algorithms. The bottom-up approach can be complex, which may make it difficult for novice developers to write AI programs.

    What are the tools that make this programming language used for building highly performant AI models?

    4. Julia

    Julia is a young, high-level dynamic programming language that was specifically designed to address the needs of high-performance numerical and scientific computing, making it an excellent choice for AI creation. Julia is fast and efficient, thanks to its just-in-time (JIT) compilation and multiple dispatches, which allow it to compile code on-the-fly for specific data types and optimize it for performance.

    It is designed to work well with existing code and libraries, easily integrated with different languages and tools. It has a simple syntax and is easy to learn for those familiar with other programming languages like Python or MATLAB. It is flexible and can be extended to support new features and applications as needed. But as a new programming language, it has a relatively tiny community of qualified developers.

    Julia has built-in support for parallel computing, making it easy to use multicore CPUs, clusters, and GPUs to speed up computation. It also supports distributed computing, making it possible to scale up computations across multiple machines.

    With the following tools, Julia has rightfully considered one of the most used common programming languages for building AI applications:

    5. JavaScript

    JavaScript is a popular language used for developing web applications, but it also has the potential for AI programming. JavaScript is a universal language, and with the help of Node.js, it is usually used for server-side programming. That opens up possibilities for building scalable and distributed AI systems.

    JavaScript also has the advantage of being a widely used language, which we covered in the article “TOP-10 The Most Popular Programming Languages 2023” in detail. It means a large community of developers that can share knowledge, collaborate and contribute to the development of AI tools and applications.

    Furthermore, JavaScript can be used to create interactive data visualizations and user interfaces, which can help present and interact with AI-generated outputs. It could be particularly beneficial for applications that involve natural language processing, sentiment analysis, and image recognition.

    Additionally, several libraries and frameworks are available for machine learning in JavaScript:

    6. Golang

    Go, also known as Golang, is another modern programming language that is designed to provide a balance between simplicity and performance. Although it wasn’t originally created for AI development, it has some features that make it a good choice for building machine learning models and other AI applications.

    One of the key strengths of Go is its excellent support for concurrent programming. It lets developers write highly concurrent and parallel programs quickly. That makes it well-suited for developing large-scale ML applications that require processing large amounts of data in parallel.

    Another advantage of Go is its speed. Go is a compiled language that produces highly optimized binaries faster than interpreted languages like Python. That makes it ideal for developing high-performance AI applications, such as real-time image and speech recognition systems.

    The Go standard library includes packages for working with data formats like CSV, JSON, and XML, making working with data from various sources easy. Finally, Go strongly focuses on code readability and maintainability, making it easy for teams to collaborate on AI projects. Simple syntax and a straightforward approach to programming can reduce errors and make code easier to understand and maintain over time.

    Golang has a growing number of AI-related libraries, including packages for machine learning (GoLearn), natural language processing (GoNLP), and computer vision (GoCV):

    programming languages for AI
    The most commonly used programming languages for AI today

    How Academy SMART can help you

    Our custom software development practice has been tasked several times to build AI and machine learning applications in manufacturing, healthcare, fintech, and e-learning areas. With this invaluable experience, we are well aware of the advantages of equipping modern software products with an effective data processing system using artificial intelligence and what benefits this gives the application in the fierce competition in the market today.

    As a reliable outsourced software development service provider, we offer a qualified team of AI application developers and a responsible project manager who will guide you from an idea to a ready-to-release product, and a competitive offshore price in Ukraine.

    You may also be interested in our offer to expand your workforce with experienced programmers in developing AI and ML systems as outstaffers. In the shortest possible time, we are ready to communicate with you strong specialists in Python, Java, Go, and JavaScript who will significantly strengthen your internal team’s capabilities

    Is it time to use the power of artificial intelligence in your enterprise? We are confident to be of service, so let’s discuss your business challenges.

    Programming languages for AI: Frequently Asked Questions

    Is AI coded in Python?

    Python is the most popular programming language for artificial intelligence and machine learning today, but it is not the only one. Other programming languages such as Java, C++, Julia, and Golang are also used for AI programming.

    Can you make AI with C++?

    C++ is a high-performance programming language suitable for developing complex AI algorithms and applications. But creating AI models with C++ requires more low-level programming and time to code than languages like Python.

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