The evolution of Artificial Intelligence has increased incredibly in the past few years, and all this was because of the various programming languages that have helped developers create intelligent systems, from simple automation scripts to the most sophisticated Machine Learning models.
Look at some of the best languages for AI development and understand the concept of programming languages for AI with this blog.
List of programming languages for AI
The best languages for AI are listed below
Python
- Python is, undoubtedly, the most popular language used for developing AIs because of its simplicity and readability.
- It has a rich ecosystem of libraries and frameworks like TensorFlow, Keras, PyTorch, and Scikit-Learn, which make a developer's job easy to implement AI algorithms.
- Its wide community support system in Python assures continuous improvement and help for the developer.
Java
- Java is a universal, comprehensively used high-performance, and scalable programming language.
- It is an excellent option when it comes to developing large-scale Artificial Intelligence systems.
- With frameworks such as Weka, Deeplearning4j, and MOA, a variety of very impressive tools in machine learning and data mining are being implemented by Java.
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C++
- High performance and efficiency are the hallmarks of this language
- Most AI applications require real-time processing, as in robotics and gaming.
- In this language, very fine control is exercised over the system resources and memory, which provides optimum performance.
- There are comprehensive libraries, such as Dlib and Shark, that support machine learning in C++.
JavaScript
- JavaScript is majorly known for development on the Web, but lately, it also become very popular in AI development, exactly in client-side applications.
- With libraries like TensorFlow.js, a developer can create and train machine learning models directly in a browser and enable the interactivity of AI-backed web apps.
Julia
- Julia is a high-level, high-performance programming language for numerical and scientific computing.
- The ease of Python joins the speed of C++ in this language; therefore, Julia is very suitable for AI research and development.
- Julia's libraries, including Flux.jl and MLJ.jl, provide comprehensive tools for machine learning.
The selection of the adequate programming language for AI development will depend on individual aspects like specific applications, performance requirements, or just personal/team expertise.
Python will continue to be preferred for its simplicity and a wide range of libraries, while Java, C++, JavaScript, and Julia, all bring different benefits to different aspects of artificial intelligence development.
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FAQs (Frequently Asked Questions)
Q.1. Which programming language is best suited for an AI development beginner?
Ans: Python is generally recommended for beginners because of its simplicity and abundance of resources and community support available.
Q.2. Can one develop AI using JavaScript?
Ans: Yes, you can use JavaScript to develop AI, more so in a scenario of developing AI-infused web applications. Libraries like TensorFlow.js make the process much easier.
Q.3. Why is C++ preferred for real-time AI applications?
Ans: C++ is a high-performance, efficient language because it finds its application in real-time AI-based applications such as robotics and gaming that work at fast speed and have reliable processing.
Q.4. How does Julia stand against the rest in developing AI?
Ans: Julia has provided the worlds of ease offered by Python, with the speed brought by C++. This feature makes it incomparable in numerical and scientific computing.
Q.5. What is the oldest programming language in AI development?
Ans: Lisp remains the oldest programming language marking its significance in the history of AI applications.
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