Artificial Intelligence (AI) has brought transformation into business operations across industries. It has become an integral part of our daily lives today. We can provide many use cases where AI simplifies the process workflow, from autopilots for self-driving cars to using robots to handle warehouse jobs, implementation of chatbots in customer care portals, and more.
The AI technology implications for business processes in various sectors are enormous. That is why the need for skilled, reliable partners to build AI-based applications is skyrocketing in recent years. However, to get a user-friendly, innovative, cost-effective solution within the timeframe, you must choose the right programming language.
It is challenging to determine the best programming language for AI because the app development process relies on the desired functional requirements, usage, and many other factors. In this article, we highlight the top AI programming languages. It is along with why Java is the best among them.
The five most common languages used for the AI projects are:
- Python – It has a simple syntax and is easy to learn. Developers can use Python’s object-oriented, functional, and procedural programming styles to complete the project in shorter development time compared to other languages.
- Java – This multi-paradigm language also follows the object-oriented programming principles. Java is simple to use and debug. Its Write Once, Run Anywhere (WORA) model allows you to run the code on different platforms without recompilation. Apart from building enterprise-grade applications, Java is ideal for projects based on neural networks, search algorithms, and genetic programming.
- C++ – With a rich collection of library functions and programming tools, C++ provides a plethora of features to develop AI software. C++ is also an object-oriented, multi-paradigm programming language, which is extensively used in developing computer games.
- Prolog – Introduced in 1972, this logic programming language offers features such as tree-based data structuring, automatic backtracking, pattern matching & unification, and more to develop AI-based applications, specifically for natural language processing. Developers use prolog to create healthcare solutions, as well.
- Lisp – It is one of the oldest languages used in AI development. While working with Lisp, programmers use compilers instead of interpreters, which enables fast & efficient coding.
All of these programming languages come with unique features to enable efficient artificial intelligence program development. However, Java is emerging as a most-preferred option by businesses and developers.
Let us find out why.
Benefits of Using Java as AI Programming Language
We have highlighted that Java is object-oriented and scalable. It offers many features to address different business needs. You can use it to create robust machine learning solutions, multi-robot systems, neural networks and other projects on AI.
A few key advantages of the languages are listed below.
- It is cross-platform, which means you can develop large-scale applications targeted to different platforms such as Windows, Linux, Android, iOS, and more efficiently.
- Has in-built garbage collector that deletes useless data automatically
- The Swing and SWT (Standard Widget Toolkit) helps you create excellent, user-friendly app interfaces and graphics.
- Has extensive community support to solve issues or queries at any time
- Multiple free tutorials are available online to know how to utilize the capabilities of Java as a programming language.
Java offers virtual machine technology, which makes it portable, transparent, and easy to maintain. It supports different coding types of algorithms to make AI application development easier.
Below are some useful Java tools for AI, machine learning, and deep learning.
TensorFlow
TensorFlow supports Java with an API. Though it is not as feature-rich as other fully supported languages like TensorFlow Python API, it is being improved rapidly. You can also check TensorFlow – Java’s GitHub repository to know more about its usage and support.
Neuroph
It is a Java-based, object-oriented neural network framework. This open-source platform offers a Java class library and Neuroph GUI to help create artificial neural nets quickly & efficiently.
Deep Java Library
Developed by Amazon, this Java-focused development tool facilitates creating and deploying deep learning abilities into the system.
OpenNLP
It is a machine learning toolkit by Apache for natural language processing. You can find the API documentation on the official website to understand its usage and functioning.
Java Machine Learning (ML) Library
An open-source Java framework that offers various ML algorithms to build smart applications in less time.
Now, let us look at a few popular Java-based AI projects:
- Robocode
It is a Java-based artificial intelligence application that helps students and Java developers grow their Java programming skills. Here, they can create a robot that looks like a tank to move around and destroy other tanks. By creating a simple robot code and implementing behavior strategy, you can build ideas for leveraging the programming intelligence to create engaging apps. - Weka
Written in Java, WEKA is open-source software. It provides various tools for data pre-processing, implementing ML algorithms, and visualization to solve real-world data mining problems. - Joone (Java Object Oriented Neural Engine)
This neural network framework helps users build new modules to implement new architectures or algorithms for creating different types of AI applications. It offers features such as- Supervised learning
- Time-delay neural networks
- Resilient back-prop
- Standard back-prop
- Recursive neural networks
- Feedforward neural network
- Unsupervised learning
- Principal component analysis
- Kohonen SOMs
- Modular neural networks
- Powerful built-in data pre-processing mechanism
- JavaScript capability to add custom behavior to neural networks
- Supervised learning
The three AI projects mentioned above would help you understand more about using Java as an AI programming language to visualize new app concepts and transform your existing systems.
Make the Most Out of Java for Your Business
Java offers a diverse range of features and tools, along with machine learning and automation capabilities that help build custom applications as per your business needs. It enables you to provide excellent user experiences on modern, interactive apps to attract and retain more customers and drive profitability.
Conclusion
We hope this blog helped you understand why Java is the preferred programming language by businesses and developers to create AI applications. If you wish to develop intelligent products or applications by integrating smart technologies, approach an experienced Java development company. They would help you with an AI-powered software solution built according to your business requirements and goals.
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