AI is an innovative technology that makes our lives easier and more comfortable. Recent studies show that enterprises invest significant money in the Artificial Intelligence sector.
According to other research by Oberlo, 91% of leading companies have already invested in artificial intelligence. Additionally, they claim that 62% of customers are willing to disclose information if doing so will enhance their interactions with a company. Their programming language demands have also increased with the increasing demand for AI. Read the article to learn about the top programming languages for AI development.
Best Programming Languages For AI Development
The best programming languages for AI assist in developing the most promising areas of the best programming languages for artificial intelligence. “Artificial Intelligence programming language” is a computer language developers apply in AI research.
Developers look into, test, and employ the computer language used in artificial intelligence capabilities to satisfy more organizational and human needs. As it says, inventions are born because of necessity.
The best programming language to utilize for artificial intelligence will be a topic of ongoing discussion. Java, Python, Lisp, Prologue, and C++ are the best programming languages for AI that can satisfy various software development and design needs. The developer must choose the finest language for artificial intelligence to meet the requirements for the functionality and features of the application.
Here is the list of the top ten programming languages for AI development.
Python is one of the most widely used languages for artificial intelligence. It is a high-level, all-purpose programming language. It makes considerable use of indentation to make its code easier to read. Python’s object-oriented approach and use of language elements facilitate the creation of logical and understandable code for small- to large-scale AI projects.
The language has many features that improve the quality of life and simplicity of use, and Python’s syntax is incredibly versatile. Python is intuitive enough for non-programmers as well. This low entrance barrier is crucial since many data scientists and analysts who work with AI don’t have significant experience and programming backgrounds.
Python is a popular choice for developing AI because of the libraries it offers, including TensorFlow, Keras, PyTorch, Scikit-learn, PyBrain, and MXNet, among others. Google, Amazon, NASA, Reddit, Instagram, Intel, IBM, Facebook, Netflix, JP Morgan Chase, and other well-known businesses are just a few examples of those that employ Python.
Some top reasons why Python is the top language for AI development-
- With Python, you will get various libraries and tools available.
- Although implementation is necessary, it enables algorithm testing.
- An increase in a programmer’s productivity thanks to object-oriented design.
- Java and C++ both evolve more slowly than Python.
One of the first languages used to build AI is called Lisp. Since its creation in the 1960s, it has been a flexible and smart language. Lisp is the right choice if your project requires code modification, problem-solving, rapid prototyping, or dynamic development.
It has several qualities that are essential for AI projects to succeed, including prototyping quickly, dynamically produced objects, Programmes can run on data structures, Data can be adjusted to change programs, using recursion rather than iteration as the control structure, outstanding symbolic information processing capability, Interactive programming made easier with the Read-Eval-Print-Loop and many more. Routinic, Grammarly, and DART are some examples of successful Lisp-based projects.
One of the best programming languages for developing AI that you will find currently in the market is Java by Oracle. This language has evolved to represent the most recent advances in science and technology. Java simplifies complex projects and is easy to use and debug for AI development. Using images to depict the data may improve user involvement.
Java has several libraries and frameworks available for AI development, including Apache OpenNLP, Java Machine Learning Library, Neuroph, Deep Java Library, MLlib, and more. Numerous companies, including well-known ones like Google, Uber, Netflix, Airbnb, Instagram, Amazon, Spotify, and others, use Java.
Bjarne Stroustrup created C++ in 1985 as a general-purpose programming language, and it has grown significantly since then. It is a quick, potent language that is well-liked among game developers. It is well-known, well-documented, and has a wide range of applications. It is also quite effective.
Caffee, Microsoft Cognitive Toolkit (CNTK), TensorFlow, DyNet, OpenNN, FANN, Shogun, and mlpack library are just a few of the AI and ML frameworks available in C++. Walmart, Google, Accenture, Twitch, Telegram, and Lyft are just a few of the well-known organizations that employ C++.
R is a statistical programming language and one of the best options for tasks requiring statistical calculations. R is a popular programming language for creating statistical software, conducting data analysis, and visualizing data, as it is simple to analyze massive data sets.
It contains a wide variety of packages and interfaces nicely with other languages. It is fantastic for AI with robust data processing requirements. Numerous businesses, including those in education, finance, telecommunications, pharmaceuticals, and the life sciences, have adopted the language.
AI solutions dealing with numerical analysis and computational science are well suited for Julia, a high-performance, dynamic programming language. In 2012, Viral B. Shah, Stefan Karpinski, Alan Edelman, and Jeff Bezanson created Julia, a programming language that allows concurrent, parallel, and distributed computing. Julia gives you the necessary capabilities for flawless execution to create a dynamic interface, eye-catching graphics, or data visualizations.
Julia provides several AI and machine learning package options. Flux.Jl, Knet.Jl, Mocha.Jl, TensorFlow.Jl, ScikitLearn.Jl, TextAnalysis.Jl, MXNet.Jl, DecisionTree.Jl, Merlin. Jl, and LossFunctions.jl are a few of them.
Haskell is a statically-typed, entirely functional general-purpose programming language. It boasts of being the first programming language to introduce ground-breaking novel features like type classes that permit type-safe operator overloading. It was primarily created for research, education, and industrial applications.
Lazy evaluation, pattern matching, lambda expressions, list comprehension, type classes, and type polymorphism are just a few of the capabilities that Haskell offers. Agda (a proof assistant), Cabal, Darcs (a revision control system), Git-annex, Pandoc, TidalCycles, Cryptol, Facebook’s anti-spam programs, and the Cardano blockchain platform are just a few examples of popular Haskell applications.
Programming in Logic is also known as Prologue. In 1972, a rule-like variant of the language was devised. Computational linguistics and artificial intelligence projects are where it is most frequently used.
The declarative programming language Prologue is ideal for creating AI systems. It is famous mainly in logic-based programming, the basis for developing AI. It is used in various free and paid applications, including tabling, hashing, and tail call optimization (TCO). These applications include systems like B-Prolog, XSB, SWI-Prolog, YAP, and Ciao.
Scala makes code quick, simple, and significantly more efficient. The Scaladex index, which contains Scala libraries and resources, aids developers in producing high-quality applications. It supports the Java Virtual Machine (JVM) environment and aids software developers in creating intelligent applications. Scala has various capabilities, including pattern matching, fast functions, browser tools, and customizable interfaces. It is compatible with Java and JS. Scala is one of the most excellent solutions for developing AI and has impressed developers in that field. Other characteristics include:
- A data science library called Smile contains algorithms for tasks like classification
- Many frameworks and libraries, including Breeze and BigDL.
Must Read: Difference between general AI & narrow AI
Avoidable Programming Languages In AI
You will find numerous programming languages for AI. You must know which programming languages will be obsolete in 2023 if you want to pursue a coding profession and improve your skills. Here, we will present the top programming languages you should avoid in AI. Let’s have a look:
PHP does not refer to a suitable programming language for AI development because of its complex debugging processes and significant deployment challenges. Nevertheless, it can be combined with Python or Java to create AI applications that need to connect to databases or integrate with the web.
Earlier, Ruby was one of the most popular programming languages, particularly when developing online applications, processing data, automating processes, etc. However, Ruby has lost its allure since Python, which is renowned for good readability and code security. So, In the coming years, you must avoid Ruby.
Do you know why we have added the C programming language to the list of obsolete ones? Well, outdated libraries, a verbose nature, and complicated syntax are the causes. Developers have switched because of Swift’s simplicity in application development and code readability.
Fortran is on the list of outmoded programming languages because it lacks dynamic memory, reliability, and unsafe code that is vulnerable to cyberattacks. That’s why developers are switching to other programming languages quickly. In 2023, we suggest not using the Fortran programming language for AI development.
Explore The Use of AI in Your Next Project
Artificial Intelligence is a vast field. Daily, you use various machines to simplify things, from shopping to scheduling appointments. So what happens when your robots are intelligent enough to anticipate your requirements and provide them without prompting? Such a possibility is lovely from a personal standpoint. There is considerably more to get thrilled about on a corporate level. Building effective AI software requires more than just implementing one of the top programming languages in your tech stack.
Finding a team to ensure the success of your project is the first step. Parangat’s role is to assist you in assembling that squad.
To learn more about what Parangath can do, contact us immediately!
With roll up sleeves, dive in and get the job done approach, it was in the year 2010 when Sahil started Parangat Technologies. Emphasizing a healthy work culture and technology-driven company, he has successfully created a workplace where people love to work and live. He is a software engineer and a passionate blockchain enthusiast.