Learn how JavaScript, C++ and R fit into AI development

Ben Wodecki, Jr. Editor

May 5, 2023

10 Min Read
Jorg Greuel/Getty Images

At a Glance

  • AI Business breaks down the leading languages being used to create AI applications.

Generative AI has thrust AI into the spotlight, with companies large and small around the world wanting to know how to get in.

For developers, the AI boom of 2023 poses a golden opportunity to work on major projects as their services become highly sought after.

But for those not in the know, it can be difficult to work out where to start and what to use. AI Business has broken down seven of the top programming languages used in AI, where to practice using them and what they can be used for to give you a leg up on the competition.

1. Python

What is Python used for in AI?

Python is among the most common programming languages and arguably the most popular one used to build AI. It is a general-purpose programming language, meaning it can be applied to a variety of potential programming needs across AI, including machine learning, deep learning and computer vision.

Python can be used on Windows, Linux/UNIX and macOS.

Where can I access Python?

Python can be downloaded from the Python Software Foundation’s website for free. Third-party Python packages are also accessible via the website.

Frequently used libraries

PyTorch – Created by Meta and operated by the Linux Foundation, PyTorch is a library containing tools and frameworks for applications such as computer vision and natural language processing. It is open source − becoming a nonprofit last September − and has been used in the development of deep learning software including Tesla’s AutoPilot and Hugging Face's Transformers.

TensorFlow – Created by AI researchers from Google, TensorFlow is an open source library for machine learning and AI, containing a variety of resources including training tools and items to help with model deployments.

Keras – Created by the renowned AI researcher François Chollet, now of Google, Keras is a library containing Python interfaces for artificial neural networks and can be used on top of TensorFlow.

Where can I try out Python?

Introduction To Python Programming – A great place to start for beginners. This Udemy course can be accessed from a browser and teaches the very basics of Python and teaches you how to create functions and scripts.

Codeacademy – Codeacademy offers a hands-on environment where users can interact with real code to learn and improve.

DataQuest – Instead of video tutorials, DataQuest offers interactive tutorials for Python, including a general-focused course as well as a machine learning-specific option.

There is a host of YouTube channels designed to help if you are stuck.

2. Java

What is Java used for in AI?

Java is a programming language that can run on a wide variety of devices including computers, gaming consoles and medical devices.

Java has been used in AI development since the mid-1990s, and developers from the likes of Twitter, Amazon and Uber have utilized Java to build a variety of AI applications.

Where can I access Java?

Java can be downloaded from its website for free for personal use. Java can also be used in development, with dev kits and other tools available here.

Frequently used libraries

Apache Commons – Apache Commons offers reusable open source Java software. It is designed to provide tools so developers do not have to utilize multiple software libraries at a time. The Apache Software Foundation, which operates Apache Commons, also houses Apache Jena, an API for extracting data initially developed by researchers at HP.

Guava – Developed largely by Google, the open source library that provides tools to make Java-based programming easier. Google’s internal developers rely on some of the libraries found in Guava, including concurrency libraries and caching, among others.

PowerLoom – PowerLoom provides language and environment for building Java-powered knowledge-based applications.

Where can I try out Java?

Java for Beginners – for those with little Java experience, Java for Beginners offers simple classes, including helping those building Android-focused applications.

CodeGym – Hitting the gym never got so technical. For those with some experience, CodeGym offers a handful of Java-focused programming tasks, as well as games and quizzes to help all kinds of learners.

Test Automation U – For those with a specific use case in mind, Test Automation U allows users to test out Java, including for visual AI applications.

3. Javascript

What is Javascript used for in AI?

Javascript is not among the most commonly used languages for AI, but it has its place given its familiarity − Javascript has been around since the early days of the internet, and most websites utilize it in some way, shape or form.

For AI, Javascript is faster than Python and can be used to add machine learning to web-based applications.

Where can I access JavaScript?

Unlike the other programming languages on this list, most web browsers have JavaScript built into them – meaning no external downloads are needed to access it.

Frequently used libraries

TensorFlow.js – A JavaScript-specific version of TensorFlow, this library is designed for developers to use ML in their browsers. It hosts tutorials, models and demos.

Synaptic – This JavaScript neural network library was developed by MIT. It can be used both in the browser and via Node.js. It can be used to build and train neural network architectures, with users able to import or export networks.

Brain.js – Similar to Synaptic, Brian.js users can develop JavaScript-powered GPU-accelerated neural networks for browsers and Node.js. Brain.js offers tutorials to help those trying to build and includes a host of examples of pre-built applications.

Where can I try out JavaScript?

Both Brain.js and Synaptic can be used to build your own ML applications.

For those wanting to start from scratch, Codeacademy’s Javascript course navigates the basics with hands-on tutorials and includes more complex concepts for learners wanting a challenge.

JavaScript Playground from Playcode is another tool to try if you want to fool around with JavaScript. The sandbox tool enables users to try out JavaScript for prototyping or simply trying out ideas.

4. C++

What is C++ used for in AI?

Another popular programming language for machine learning, C++ is not quite as widely used as Python but it is still used across AI.

C++ is best applied to embedded systems and robotics as it can interact with low-level hardware while providing real-time performance.

Where can I access C++?

To access C++ on Windows or Linux, users will need to download Virtual Studio, which provides access to the programming language as well as a platform to test it.

To access C++ on Mac, you will need to download Xcode from the App Store.

Frequently used libraries

TensorFlow C++ - TensorFlow has a host of C++-focused APIs.

Caffe – Designed for C++ with a Python interface, Caffe was built by Yangqing Jia, president of the Alibaba Cloud's Computing Platform. Caffe includes a deep learning framework, along with an architecture and an active community of developers supporting it.

Shogun – This open source ML library offers a variety of C++ methods that can be used alongside interfaces from Python, R and Lua. Shogun hosts a collection of varying data representations, algorithm classes and general-purpose tools for prototyping data pipelines.

Where can I try out C++?

The earlier mentioned Vision Studio makes for a sensible place to try out C++ given it is required to access it via Windows.

Another option for trying C++ is Eclipse, an open source integrated development environment where users can test out C++ tools on Windows, Linux and macOS that can debug and compile code, as well as auto-generated code while editing, similar to tools like CodeWhisperer or Copilot.

5. R

What is R used for in AI?

Like most of the programming languages on this list, R is best applied to machine learning use cases, such as image recognition, natural language processing and sentiment analysis.

However, R can also be used to build supervised and unsupervised learning models because R is suitable for use with sizable amounts of data. It is also applicable to a variety of data mining tasks.

Where can I access R?

R can be downloaded from the R Project website. Users need to decide their preferred CRAN mirror. R can run on a variety of UNIX platforms, as well as Windows and MacOS.

Frequently used libraries

Dplyr – Dplyr contains a variety of tools for data manipulation, including filtering and summarizing capabilities.

Lubridate – This R package is designed to make it easier for models and applications to work more effectively with dates and times.

Mlr3 – This R-focused library contains tools and frameworks for using R in machine learning development.

Where can I try out R?

DataQuest – DataQuest is not just applicable to Python, it offers similar courses for R.

RStudio is another option. This integrated development environment is dedicated to R and can be accessed via a free download for desktops. It can also be used via RStudio Server on a remote server, allowing for RStudio to be used via a web browser.

There are also recorded tutorials and talks from R Project conferences available on YouTube.

6. Julia

What is Julia used for in AI?

Julia, like Python, is a general-purpose programming language. Julia can be used for numerical analysis and computational science as well as machine learning.

Julia was built to operate at a high level and pace and is the youngest programming language on this list, having only been launched back in 2012 by a team of renowned computer scientists including Jeff Bezanson, Stefan Karpinski, Viral B. Shah and Alan Edelman.

Where can I access Julia?

Julia can be downloaded via its website. It is usable on Mac, Windows and Linux.

Frequently used libraries

The best way to access Julia tools is the general registry, which contains over 9,000 packages.

There is also JuliaHub, which allows users to search all registered open source packages and codes, and Julia.jl, a manually curated taxonomy of Julia packages.

Where can I try out Julia?

The team behind Julia created a web-based interactive Julia shell that users can try out.

As Julia is early in its life, there is not too much in the way of external places to try out the language. However, the Julia team has created a test suite to verify functionality across multiple platforms.

7. Haskell

What is Haskell used for in AI?

Probably the least well-known on this list, Haskell ranked the 28th most popular programming language searched on Google in 2021.

However, this general-purpose programming language can be used in developing machine learning systems and can prove effective for handling inconsistent data.

Where can I access Haskell?

Haskell can be used on Linux, macOS, FreeBSD, Windows or WSL2 and can be downloaded from GHCup.

Frequently used libraries

The Haskell website has a handful of basic libraries for Haskell.

A popular Haskell library is Prelude, which hosts a variety of tools and functions applicable to the programming language.

Where can I try out Haskell?

The Haskell website offers a variety of links to follow as to where to try out Haskell, including an in-depth introduction that covers the language and how it works in detail.

For beginners, the book Haskell from the Very Beginning provides a complete overview and tells you how to get started.

And the University of Oxford offers short courses teaching functional programming of Haskell for those wanting a hands-on way to learn.

For users wanting to get hands-on with Haskell themselves, the Haskell Language Server can be downloaded via GitHub and acts as an integrated development environment to play around with the language.

About the Author(s)

Ben Wodecki

Jr. Editor

Ben Wodecki is the Jr. Editor of AI Business, covering a wide range of AI content. Ben joined the team in March 2021 as assistant editor and was promoted to Jr. Editor. He has written for The New Statesman, Intellectual Property Magazine, and The Telegraph India, among others. He holds an MSc in Digital Journalism from Middlesex University.

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