The 10 Best Programming Languages for AI Development

In 2022, we will witness more strategic adoption of AI with breakthroughs and AI-literate environments wherever possible. AI continues to push boundaries of what’s possible with the help of data, tools, and programming languages. While we can’t exactly define what’s best as it’s more subjective than selective, we have tried our best to cover top languages that are used to create AI solutions. It was one of the popular languages for agile software development, rapid application development , and software design patterns. It was highly influential in GUI, font editors, desktop metaphors, and IDEs.

It is one of the most flexible programming languages with automatic garbage collection, quick prototyping abilities, dynamic object creation, and support for symbolic expressions. LISP was used to express the earliest AI programs such as ELIZA. An interesting feature of Julia is that it can easily translate algorithms directly from research papers into code, allowing reduced model risk and increased safety. It is a high performance AI programming language built for modern AI applications and is ideal for developers with a background in Python or R.

Julia

The work of specialists in these areas is aimed at the same result, but the methods of achieving it are different. In the case of ML, you must know everything related to data processing, for example, the TensorFlow library. Businesses use this technology to solve complex problems or automate forecasting and data processing. It is indispensable in digital marketing when it is necessary to personalize the customer experience and study their behavior. It is also used in healthcare to process big data, diagnose diseases, determine risks, and adjust treatment. Predicting the mortality of COVID-19 patients with this technology is 92% accurate.

This post lists the ten best programming languages for AI development in 2022. The IntelliSoft team is long enough in AI and machine learning development to talk about intelligent technologies. Once, we developed an AI-based fuel consumption forecasting model for one of our clients. We also empowered our solutions with IoT devices that send notifications when the fuel runs off and automatically order fuel and create invoices.

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Java is another language that’s extensively used in AI development. As an object-oriented language with easy debugging and simple syntax, Java has a proven track record in software development. Java’s fast execution makes it especially well-suited for applications that require processing large amounts of data. One of Java’s biggest advantages is its use of a virtual machine, which allows developers to implement it easily on a variety of platforms. Python is one of the most popular AI programming languages due to its versatility and longevity.

• When it comes to AI development, Java offers several libraries and frameworks such as Apache OpenNLP, Java Machine Learning Library, Neuroph, Deep Java Library, MLlib and so on.
• If you want to program applications that require data analysis and representation, R is the best alternative we can advise you.
• TensorFlow.js is a JavaScript framework for training and deploying machine learning models in the browser and Node.js.
• Learn about the latest trends in software development and content of interest in technology.
• In short, you don’t have to reinvent the wheel – just determine what type of ‘learning’ the AI will do.
• Because C++ is a low-level language, it converts user code to machine-readable code.

The language is syntactically identical to C++, but it provides memory safety without garbage collection and allows optional reference counting. Although Julia’s community is still small, it consistently ranks as one of the premier languages for artificial intelligence. The language has more than 6,000 built-in functions for symbolic computation, functional programming, and rule-based programming. C++ is a low-level programming language that has been around for a long time. C++ works well with hardware and machines but not with modern conceptual software.

What factors will affect performance and scalability?

Moreover, best languages for ai simplifies the scaling of projects, which is a priority for many machine learning engineers. The Java Virtual Machine improves productivity by allowing engineers to write efficient code on multiple platforms for machine learning at once. Even outside of mobile apps, Java has quite a few machine learning libraries for deep learning and natural language processing. Java almost always ranks second after Python as the best language for AI. Its best quality makes it one of the top candidates for AI development, such as easy debugging and simple syntax. Furthermore, Java offers excellent production value, smooth integration, quick execution, and fast runtimes, all of which AI requires.

Deciding which language suits you best depends on many factors, from what it is about, your background, and your level of comfort with these languages. It’s a well-developed, simple and consistent programming language that includes conditionals, loops, user-defined recursive functions, and input/output facilities . In that case, it may be easier to develop AI applications in one of those languages instead of learning a new one.

Is Python enough to learn AI?

It should be self-explanatory as to why these projects would appeal to a growing business such as yours. Majority of artificial intelligence projectsare market-oriented. Aside from the 2001 science fiction film with Haley Joel Osment, artificial intelligence is a complex and profound subject area. Recruit high-performing development teams managed by Trio’s engineering managers.

For example, in the case of machine learning, you might choose Python, which is a great choice for this AI subset. Smile – a data science library with algorithms for actions like classification. Overall, it represents everything as symbolic expressions, making it easier to develop intelligent systems with any data type. Smalltalk features dynamic runtime typing methodology and maneuverability. In this language, there is no concept of integers, characters, and booleans — all these are treated as objects. However, the most important factor is the community – It’s an open-source language, licensed under the liberal MIT license.

Use AI in Your Next Project

Lazy evaluation and the list and LogicT monads make it easy to express non-deterministic algorithms, which is often the case. The language’s features enable a compositional way of expressing the algorithms. The only drawback is that working with graphs is a bit harder at first because of purity. Python is the most used programming language to develop AI applications. YouTube, Instagram, Pinterest, and SurveyMonkey are all built using Python. Let’s dive into the programming languages ​​you can use for AI projects.

Prolog is a declarative language where programs are expressed in terms of relations, and execution occurs by running queries over these relations. Prolog is particularly useful for symbolic reasoning, database and language parsing applications. It’s free, we don’t spam, and we never share your email address. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming asponsor. With a plethora of opportunities for both application and development, it is safe to say that Artificial Intelligence has found a profitable place in the business world. Popular applications of Haskell include Agda , Cabal, Darcs , Git-annex, Pandoc, TidalCycles, Cryptol, Facebook’s anti-spam programs and Cardano blockchain platform.