Which AI development language is best? This is a question easier said than answered as it depends on organizations’ needs. Every language has its own pros and cons but what are they and how can organizations discover which one works best for them?
What 2024 AI trends should companies focus on? LLM development? Maybe generative AI development? Well, it does not really matter if organizations choose the wrong AI development language to drive their next “intelligent” project forward.
When it comes to implementing AI into their ways of working, many organizations often choose the wrong language to base it on. And this is crucial as it is essentially like building a house on a faulty foundation. Sure, it might work at first, but as time goes on and more and more stress is placed on the AI, major problems will start to appear in the system – all because organizations failed to do their research before committing to a new AI-based solution.
So, with that in mind, which programming languages are most used for AI development? How do different programming languages impact AI project outcomes? What are the key features of a good AI development language? Are there any new programming languages emerging for AI development and how do programming language choices affect the speed and efficiency of AI development?
The following article will answer all of these questions but before it does, it should explore some different types of programming language and what they offer before moving on to which languages are best suited for AI-based projects.
Understanding how are large language models trained is important – read on to find out about the programming languages you should consider using.
Examples of different program languages
It should go without saying that in today’s technology-driven world there are many different types of programming languages we could discuss. But the main AI development languages we will focus on are Python, C++, R, Java, Julia and JavaScript.
- Python: is undoubtedly an easier AI development language to learn than most. It is built around a simple, easy-to-learn syntax – making it easier for developers to write short, reliable code. And yes, coding is necessary when building an AI system – at least for now. Additionally, Python is ideal for any AI or machine learning-based projects, and it thrives more on the back-end, rather than in front-end operations.
- C++: is a little harder to use than Python as it comes with more syntax rules and conventions. Despite this, C++ is faster to use than Python through static typing processes – leading to faster code completion. Additionally, C++ is typically used in projects that involve any kind of embedded system due to the hardware-level coding that it provides to developers.
- R: is ideal for any organization that wants to build statistical techniques for AI algorithms involving probabilistic modeling, simulations and data analysis. Which is why it is the main AI development language for any type of data science application due to R’s ecosystem of packages, which enable developers to manipulate and visualize data critical for AI development.
- Java: is one of the main languages developers use to integrate AI with existing systems. The main reason for this is an extensive ecosystem that provides libraries, tools, stable runtimes and cross-platform portability to developers. Java makes it much easier to build and deploy AI apps that work across different hardware and software than other key AI development language types.
- Julia: is mainly leveraged by an organization interested in data science prototyping, often in combination with Python, which itself is the language that brings the code produced by Julia to life. However, even though Julia needs either Python or R to ensure what it produces works for developers, it is still one of the main languages leveraged by engineers, analysts and scientists due to its proven computational research, time series analysis, signal processing workflows and mature mathematics and performance processes.
- JavaScript: Jis leveraged by development teams that require their AI development language to be able to seamlessly integrate AI into web platforms from end to end – JavaScript’s toolkits enable complex machine learning features to be leveraged in any browser. For example, with JavaScript, businesses are able to analyze images without having to call the back end. Additionally, Node.js enables organizations to easily host and run machine learning models leveraging serverless architectures.
These are just a sample of some of the languages that work with AI, but it was not a random selection as Python, C++ and JavaScript can each be leveraged effectively to drive efforts with one of the most successful AI platforms in the world right now – OpenAI.
Read also: What is AI Tech Stack?
Programming languages that might not be so suitable for AI
Three examples of development languages that might not work well on AI projects are Perl, Lisp and Prolog. Perl is often seen as a bad choice for an AI development language due to its general unpopularity in the development community, as well as the fact that it is mainly seen as a scripting language by those who use it.
Lisp and Prolog, meanwhile, can be used for building AI projects, but are often ignored thanks to the emergence of other more popular languages in this space already mentioned in this blog such as Python and C++.
Which programming language is right for you?
When organizations are choosing the right AI language for their next project it’s not really a question of which is better. It’s a case which best suits your needs.
Python is a safe bet for intelligent AI applications with frameworks like TensorFlow and PyTorch. However, C++, Java, or Julia are often the better choice if organizations are looking to build specialist AI-based systems with intense computational demands.
But even if you already know what development language works better for you the question remains, “where do you start?” At Software Mind, we know that implementing AI is easier said than done, and we also know that undertaking this kind of work for those not in the loop when it comes to technological trends can be extremely daunting.
That is where our experienced software experts come in. They can help choose the AI development language for you quickly and easily by connecting with you and understanding more about what you need to leverage AI for, which in turn will save you significant costs in time and money.
So, what are you waiting for? Our experienced software development team is happy to talk about what AI can do for you.
About the authorSoftware Mind
Software Mind provides companies with autonomous development teams who manage software life cycles from ideation to release and beyond. For over 20 years we’ve been enriching organizations with the talent they need to boost scalability, drive dynamic growth and bring disruptive ideas to life. Our top-notch engineering teams combine ownership with leading technologies, including cloud, AI, data science and embedded software to accelerate digital transformations and boost software delivery. A culture that embraces openness, craves more and acts with respect enables our bold and passionate people to create evolutive solutions that support scale-ups, unicorns and enterprise-level companies around the world.
