Determining the best language for AI before you start on your next software project will make the project go a lot smoother. Today, artificial intelligence is an integral part of the technologies people use every day. As the need for AI-powered software and apps grows, so too does the need for AI developers. Like all things related to software development, how to best create AI-based software and applications depends on multiple factors.
In this post, we take a look at whether software developers agree on the best language for AI and how choosing an AI programming language ultimately comes down to your project's scope and requirements.
Best Language for AI
AI allows organizations big and small to save time and money by automating and optimizing routine business processes. Recent research suggests that a growing number of companies are using AI for multiple core business practices, including enhancing workforce and customer experiences.
AI is not a specific, one-size-fits-all solution. For instance:
- If your project involves extensive data analysis, you might want to choose R, as it’s aimed at statistical computing.
- If you want a language best-suited for deploying machine-learning models in production, Python’s your better pick.
- Java is a popular choice for mobile app development, which relies heavily on AI.
Let’s explore the advantages and diverse applications of the most popular AI programming languages.
Used for a wide range of applications, including back-end development and machine learning, Python streamlines coding and makes the language easier to learn. Versatile and simple to use, this highly-popular language is an excellent choice for new and seasoned AI development engineers regardless of programming experience. Developers love its straightforward structure, exceptional documentation, and community support, as well as its broad range of pre-designed libraries that optimize the AI development process.
AI-specific frameworks developed for Python include:
- scikit-learn for training machine learning models.
- PyTorch for visual and natural language processing.
- Keras, which serves as a code interface for complex mathematical calculations.
- Theano, a library for defining, optimizing, and evaluating mathematical expressions.
Often considered the go-to language for AI-intensive mobile app development, Java is one of the best languages for AI. It offers a simple syntax, easy debugging, quicker execution and faster runtimes compared to Python. It also facilitates easy scaling of large or complex AI applications. Many popular big data processing tools like Apache Hive, Hadoop, and Spark are written in Java, allowing for smooth integration with these key analytic frameworks.
If your software or app requires numerical analysis and computational science, the Julia programming language is worth considering. While relatively new, its speed, powerful computation capacity, and script-like syntax make it a popular choice. It can seamlessly translate algorithms from research papers into code while enabling machine learning engineers to estimate a model and deploy it in production using the same language.
LISP or Lisp has a long history—it’s the second-oldest high-level programming language. It dates back to the 1950s when AI pioneer John McCarthy created it for AI programs like ELIZA, an early natural language processing computer program. Thanks to its adaptability, quick prototyping abilities, and capacity for dynamic object creation, it’s typically used in machine learning projects. Over time, many of Lisp’s distinct features have been folded into other popular AI programming languages like Python.
Developed by statisticians for statistical computing, R is a powerful, free software environment that easily crunches vast data sets, making it a top programming language for statistical software development, data visualization, and data analysis. It’s also popular for developing machine learning projects that involve model training and evaluation. Its interactive environment is ideal for rapid prototyping and experimentation with new problems.
A general-purpose programming language now widely used for competitive programming, C++ provides a fast processing speed that facilitates complex machine learning models runing with high efficiency. It excels at dynamic load balancing, memory management, and adaptive caching, making it a frequent choice when building scalable big data frameworks. If your AI application is resource-intensive and needs quick execution, C++ is an excellent option.
Building the Best Programming Language for AI
When choosing the “best” AI programming language for your project, it’s essential to:
- Keep in mind your project’s goal and deliverables.
- Assess the tasks at hand.
- Identify the resources required to complete them.
Only then can you move on to considering which AI programming language offers the tools and libraries you need to meet your project’s goals.
Zibtek applies years of experience in software development to help our clients weigh the advantages and limitations afforded by each programming language in the context of what they seek to accomplish. And we do it all with an eye towards optimizing development and reducing overhead costs.
Are you looking to build an amazing AI app that can transform your business? Get in touch with our team today to get started on turning your idea into a real AI solution based on best practices and solid expertise.