6 Best Programming Languages ​​for AI

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NLP is what smart assistants applications like Google and Alexa use to understand what you’re saying and respond appropriately. This is how the best tools create and orchestrate campaigns and gather insights to improve your effectiveness as a brand. Really, if you’ve ever worked with a digital device that didn’t know how to tell up from down or do a simple task, you’d probably quite like artificial intelligence. At its core, artificial intelligence (AI) refers to intelligent machines. If you think that artificial intelligence makes for some scary alternate realities, you’re not alone. And once you know how to develop artificial intelligence, you can do it all.


Hitting closer to home, businesses utilize AI to improve production, operations, and customer experience. This article will go over which programming languages are the best for AI and what can be done with them. That’s all about the best programming language for AI or Artificial Intelligence Development. Python has been the most acceptable and most popular language for creating AI and machine learning solutions over the last few years. Python is the most popular option among AI engineers due to its user-friendliness more than anything else.


C++ isn’t always the first choice for AI-focused applications, but it’s so widely used throughout the industry that it’s worth mentioning. This language runs and executes very efficiently, but the trade-off is that it’s more complex to write. This makes C++ a great choice for resource-intensive applications, where it is occasionally used in combination with other languages to build AI-focused applications. The Deeplearning4j GitHub provides a variety of examples of how the library operates and how to start coding using its tools. The examples page showcases many implementations of the library, from training a neural network to remember a string of characters, to deciphering captchas. The library shows the depth of what you can achieve when using Java for AI development.

  • It’s also easy to learn and master the Python language, as it is short, clear, and straightforward.
  • A modular library designed for AI newcomers is called Pybrain, which stands for Python-Based Reinforcement Learning, Artificial Intelligence, and Neural Network Library.
  • For example, TensorFlow Java can run on any JVM to build, train, and deploy machine learning models.
  • Java, C++, and JavaScript are other top contenders, but Python is probably the best all-around option for AI development.
  • It’s a reliable option for any web developer because it’s relatively easy to learn, and is a promising choice for beginners learning AI or general web development.
  • Today, AI is used in a variety of ways, from powering virtual assistants like Siri and Alexa to more complex applications like self-driving cars and predictive analytics.

It also provides a seamless integration of key analytic frameworks and an outstanding production value. Java’s Virtual Machine Technology makes its implementation on multiple platforms quite simple. With the write once, run anywhere methodology, you can develop and compose your AI application on a single platform and implement it on others. You should start the process of integrating one or more of these languages if your business needs to integrate artificial intelligence. There is no end to what AI can achieve to speed up your company’s growth with the correct development team.

Other Programming Languages for Artificial Intelligence

Others are built to perform numerical analysis, while some are excellent at natural language processing. Let’s analyze the numerous uses and benefits of the top AI programming languages and find what programming language for artificial intelligence suits you. Julia is a high-level,
high-performance programming language that makes coding fast and efficient. It’s great for AI development because it’s flexible and easy to learn.

best programming language for artificial intelligence

The programming languages we’ll be discussing presently have stood the test of time. In this article, we will discuss the top five programming languages for AI and Deep Learning that developers should learn in 2023. We will explore the features, pros, and cons of each language to help you make an informed decision. Java is a versatile and powerful programming language that enables developers to create robust, high-performance applications. Python is an interpreted, high-level, general-purpose programming language with dynamic semantics. Learning the skills to develop AI applications is critical for modern programmers.

Best Programming Language for AI and Machine Learning

Designed by Jeff Bezanson, Alan Edelman, Stefan Karpinski and Viral B. Shah in 2012, Julia supports concurrent, parallel and distributed computing. Recent studies show that businesses are investing more in artificial intelligence. The majority of these resources are open source, so anyone can use them for nothing.

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Java’s Virtual Machine Technology helps the developers build a single version of an app that they can run on other Java-based platforms. Developers can also work on the graphics and interfaces, making them more appealing with the Standard Widget Toolkit. In all, Java helps you maintain, port, and make AI applications secure. For AI development, Java offers ease of usage and debugging and simplifies large-scale projects.


If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor. The brain controls thought, memory, emotion, motor skills, vision, breathing, metadialog.com and touch. This complex structure of the brain became a source of inspiration for scientists and the concept of AI emerged. AI is the ability of a computer or robot to perform humanoid tasks.

  • This language is the first to mention when it comes to complex calculations in the scientific and technical fields.
  • Additionally, Java can develop anything ranging from deep learning to data analysis, machine learning, and natural language processing.
  • Although this technology has a myriad of approaches, the continual advancements in deep learning and machine learning are instigating a paradigm shift in all areas within the tech industry.
  • AI technology has grown in popularity, and many people are adopting it to improve their businesses and personal lives.
  • But Python has become the lingua franca of data scientists and researchers for performing experiments in deep learning.
  • Even though Prolog was one of the first logic programming languages, hence one of the oldest, it still holds its position in the industry.

Most developers consider it a great alternative for developing AI. However, Rust exempts garbage collection, and it offers additional memory safety. Among the many questions trending about AI, programming languages seem to resurface all the time. There is a need to develop this technology in order to enjoy its maximum benefits. However, this development journey begins by using an appropriate programming language. In this article, we will explore some of the ten best programming languages for AI development in 2023.

Best Programming Languages for Machine Learning

Java has been called the “jack of all trades” of programming languages. It is hugely popular with programmers and is starting to gain ground with machine learning practitioners as more programmers with a Java background enter ML. Now, Python is the leading programming language for data analytics, sentiment analysis, and data science. The language is being used by Google, meta, Dropbox, Walt Disney, and other household names.

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The fact that it has been around for so long and has consistently performed well as a general purpose programming language that can be used for front-end or beck-end development. It is easy to learn, produces clear, streamlined code, and works well for new as well as experienced developers. With a clearly defined syntax and simple English keywords, Python is highly readable, and easy to learn. AI is an automatic process where the computer can do the things that human intelligence can do.

R Programming Language

It contains various pre-existing libraries such as Pandas, SciPy and nltk, etc. Further, Python also contains simple syntax and easy coding, which makes Python the first choice of AI developers and programmers. One of the safest programming languages used for AI processes, Haskell has no room for errors. The programming language is well-known for resolving errors, during the compilation process and even before that.

  • Because of its “write once, run anywhere” programming philosophy, Java, which was initially introduced more than 20 years ago in 1995, is employed by AI programmers.
  • Another advantage to consider is the boundless support from libraries and forums alike.
  • Now it supports object-oriented, generic, and functional features besides low-level memory manipulation.
  • Developed by MIT in 2012, Julia is a relatively new AI programming language designed to effectively handle expansive numerical analysis and handle large data sets with ease.
  • From the inventions of smart assistants like Alexa and Siri to the creation of self-driving automobiles, AI will forever remain a part of our daily lives.
  • The memory safety, speed, and ease of expression make Rust the perfect choice for AI development and scientific computing.

When it was first introduced, LISP was ahead of its time, but it has mostly been replaced by other languages. However, familiarity with LISP can still help you understand AI more thoroughly and produce better results through your work. LISP isn’t the most frequently used AI programming language in a modern context, but that doesn’t mean it’s not used at all. Learning how to apply artificial intelligence is critical for many job roles, especially for those interested in pursuing a career in programming.

Best Programming Language for AI Development

Additionally, Java is a relatively safe and scalable programming language, making it an excellent choice for applications on a large scale. Regarding artificial intelligence, Java is one of the best programming languages https://www.metadialog.com/blog/best-programming-languages-to-choose-for-ai/ available due to its advantages and simple code. R is one of the great languages for statistical processing in programming. However, R supports free, open-source programming language for data analysis purposes.

Should I learn Java or Python for AI?

Java is popular among programmers interested in web development, big data, cloud development, and Android app development. Python is favored by those working in back-end development, app development, data science, and machine learning.

Other top contenders include Java, C++, and JavaScript — but Python is likely the best all-around option for AI development. Designed by Alan Kay, Dan Ingalls and Adele Goldberg in 1972, Smalltalk has influenced so many programming languages such as Python, Ruby, Java and Objective-C. According to the number of Google searches conducted for tutorials, Haskell was the 28th most popular programming language in 2021. Julia offers several packages for Artificial Intelligence and machine learning.

best programming language for artificial intelligence

However, AI development has become increasingly popular among individuals and businesses recently. AI development seems like the best option because it offers advantages like improved customer experience, intelligent decision-making, automation, fewer errors, and data analytics. When these packages are coupled with a wide range of libraries, the capabilities of the R programming language reach new heights. The programming language is preferred by top AI companies for its ability to solve complex issues. It is another easy-to-learn language used for analysis, Big Data modeling, visualization, and forecasting. It has many extensions, for example, TM is designed for text analysis.

Does AI involve coding?

Programming Skills

The first skill required to become an AI engineer is programming. To become well-versed in AI, it's crucial to learn programming languages, such as Python, R, Java, and C++ to build and implement models.

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