10 Best Programming Languages for AI Development

Alan Turing first explored the possibility of Artificial Intelligence in the 20th century and discussed building intelligent machines in his 1950 paper, Computing Machinery and Intelligence. Five years later, Allen Newell, Cliff Shaw, and Herbert Simon initialized its proof of concept via a program called Logic Theorist, which was presented at the Dartmouth Summer Research Project on Artificial Intelligence in 1956.

AI Development

Fast forward 66 years, and the interest as well as investment in developing AI, boomed significantly. The advancement in AI was made possible by the simultaneous development of data science, machine learning, and the availability of robust hardware machines.

Today, almost 77% of devices already use AI in one form or another. It is estimated that by 2023, AI-powered voice assistants alone would be able to generate a revenue of 8 billion. The global AI market is expected to reach a valuation of $60 billion by 2025.

Thus, let’s take a look at the 10 best programming languages being preferred by developers for AI development currently.

10 preferred coding languages for AI development

1. Python

Python is the first most preferred programming language for the purpose of AI development because it requires considerably less coding when compared to other languages. This is one of the foremost reasons why businesses are looking to hire dedicated python developers in recent times.

Python

A successor of the ABC programming language, Python was first designed by Guido Van Rossum at the Centrum Wiskunde & Informatica (CWI), Netherlands. It is already employed by a large number of enterprises all around the world like Google, NASA, Amazon, JP Morgan Chase, IBM, Netflix, Intel, Facebook, etc.

Reasons for choosing Python:

  • It offers pre-built libraries like Pytorch, Pybrain, TensorFlow, Numpy, and Keras for advanced computing.
  • Its modular architecture-based scripting facility; in addition to its simple syntaxes, and rich text processing tools favor AI app building.
  • Python supports cross-platform compatibility.
  • It is open-source and offers multiple forums and tutorials.

Uses of Python: Python is employed extensively in developing deep learning-based apps, AI apps, data science apps, networking apps, and for conducting scientific calculations as well as for numerical data processing.

2. Java

Java has been transforming the world of Information & Technology since 1995. Originally developed by James Gosling of Sun Microsystems, Oracle’s Java is one the most popular programming languages in the world today.

Regarded as the queen of programming languages, Java is used by Google, Netflix, Uber, Airbnb, Spotify, Amazon, Slack, etc.

Reasons for choosing Java:

  • Java offers swing and standard widget toolkits.
  • It comes with a built-in garbage collector.
  • Virtual Machine Technology lets developers create a single app version and then execute it on other Java-supported platforms.
  • It is easy to use, learn, debug, and is scalable.
  • Java is enabled with cross-platform support.

Uses of Java: Robocode, Zonal Neural Engine, and WEKA are some well-known AI projects created using Java.

3. Scala

Scala is a multi-paradigm coding language that was designed by Martin Odersky at the Ecole Polytechnique Federale de Lausanne, Switzerland, and introduced in 2004. Its source code is executed on a Java Virtual Machine. Capable of supporting both object-oriented programming and functional programming, Scala is preferred for its robust features, flexible interfaces, and browser tools.

Scala is used by LinkedIn, Twitter, Foursquare, Tumblr, Netflix, etc.

Reasons for choosing Scala:

  • Scaladex is an index consisting of Scala libraries and other resources.
  • It can deal with complicated algorithms.
  • Scala is compatible with Java & JS and supports multiple JVM libraries.

Uses of Scala: Scala is best for developing AI-intensive Android apps. It is also preferred to confluence big data processing engines.

4. JavaScript

Another popular programming language is JavaScript which was designed by Brendan Eich of Netscape and made its debut in 1995. JavaScript involves extensive coding and hence is suited for code-loving developers. An object-oriented coding language, it integrates well with CSS and HTML.

Microsoft, PayPal, Uber, and Groupon immensely rely on JavaScript.

Reasons for choosing JavaScript:

  • Supports machine learning libraries like React.js, jQuery, and Underscore.js.
  • JS performs faster and is scalable owing to node.js.
  • JS offers numerous online modules.

Uses of JavaScript: JavaScript facilitates data storage, handles frontend and backend functions, end-to-end development of websites, ERP apps, and supports the development of AI-based projects.

5. Lisp

Designed by John McCarthy, Lisp came around in the 1960s and is one of the oldest programming languages. Developed by Steve Russell, Timothy P. Hart, and Mike Levin, Lisp became the earliest language for AI development because both the development of Lisp and AI research emerged in MIT at the same time.

Alphabet, LLC, Grammarly, DART, and Boeing are some companies that have used Lisp to create various projects.

Reasons for choosing Lisp:

  • Commonly used dialects of Lisp include Common Lisp, Clojure, Scheme, and Racket.
  • Popular libraries that Lisp uses for AI and Machine Learning are LLA, CLML, and Antik.
  • Rapid prototyping, dynamic object creation, and in-built garbage collection features of Lisp make it suitable for AI app development.

Uses of Lisp: Lisp has been used for some very complex projects like CircleCI, AutoCAD systems, London Tube, etc.

6. R

R is a free and open-source coding language meant for statistical computing and graphics. It made its first public appearance in 1993 and is designed by Ross Ihaka and Robert Gentleman. R is a fundamental coding language used for data mining and data analysis.

Google, Airbnb, Microsoft, and IBM extensively utilize R.

Reasons for choosing R:

  • R lets you create your objects, functions, and own packages.
  • Supports libraries like TensorFlow, Keras, and MXNet.
  • Offers support for built-in graphic and data modeling features.

Uses of R: R finds its applications in drug advancement, health care, marketing, astronomy, medicine, big data analytics, and finance-related business.

7. C++

C++ is an all-purpose programming language first designed by Bjarne Stroustrup. C++ is also standardized by the International Organization for Standardization (ISO).

Google, Intel, Walmart, Accenture, Oracle are some organizations that actively use the C++ programming language.

Reasons for choosing C++:

  • C++ offers a myriad of libraries including TensorFlow, DyNet, FANN, OpenNN, AI-ML libraries.
  • Its polymorphic flexible programming allows it to show data in more than one form.
  • C++ is machine-independent but platform-dependent.

Uses of C++: C++ is used for programming video games, developing servers for e-commerce, desktop apps, browsers, operating systems, AI apps, embedded systems, critical apps, etc.

8. Haskell

A general-purpose, functional coding language, Haskell is named after logician Haskell Curry. Haskell comprises lazy evaluation, type polymorphism, and lambda expression.

Barclays Capital, Bank of America, AT&T, NVIDIA, and IBM are some companies that use Haskell.

Reasons for choosing Haskell:

  • Haskell offers an in-built garbage collection.
  • Haskell offers a type-checker that can validate codes right when they are being developed, which means that it can fix bugs impromptu.
  • Haskell’s open-source centralized repository called Hackage features more than 140000 packages.

Uses of Haskell: Haskell primarily finds application in academia, research, and industries. Glasgow Haskell Compiler is the primary implementation of Haskell.

9. Julia

Designed by Alan Edelman, Jeff Bezanson, Stefan Karpinski, and Viral B. Shah, Julia is one of the latest programming languages which made its debut only in 2012. Described as a dynamic coding language, it is designed for carrying out perfect numerical analysis and computational science.

Several organizations which rely on Julia include Google, Intel, BlackRock, AstraZeneca, Moderna, Pfizer, NASA, the Federal Aviation Administration, etc.

Reasons for choosing Julia:

  • Julia can easily interface with java, R, Python, C++, and other languages.
  • Offers multiple machine learning libraries such as TensorFlow.Jl, Mocha.Jl, Flux, etc.
  • Julia comes with several features like garbage collection, debugging, metaprogramming, and memory management.

Uses of Julia: Julia is a top-notch choice for developing AI apps.

10. Rust

Designed by Graydon Hoare and developed by The Rust Foundation, Rust is known as the systems programming language. Syntax-wise it is similar to C++. Rust is preferred for AI projects and is loved by developers for its speed, high performance, and safety.

Rust is a popular choice of backend development for Polkadot, Dropbox, Firefox, Cloudflare, and Azure.

Reasons for choosing Rust:

  • Rust is memory safe.
  • It can optimize the code for speed as it can be statically typed and compiled.
  • It prevents garbage collection.

Uses of Rust: Rust is quite useful for AI projects and scientific computing. It was recently employed by Google for an Android Open-Source Project.

Ultimately, how does the future of AI look?

Artificial Intelligence is undoubtedly a transformative technology that can revolutionize the future. Google is already creating an AI assistant to book appointments, and Bloomberg already employs Cyborg Technology to run complex financial reports.

While it could be said that the development of AI is still in its nascent stages, autonomous cars, virtual nursing assistants, personalized patient experience with big data, digitized textbooks, and virtual tutors are not a far-fetched dream.

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