AI Programming Languages to Strengthen Development
Read about how different artificial intelligence programming languages strengthen development.
Join the DZone community and get the full member experience.Join For Free
Today, technology has reached to the next level of advancement, encouraging Machine learning and deep learning for better personalization and recommendation. The AI enabled programming language allows smart search, voice interface, and intelligent assistance to improvise the app development. Apart from this, new techniques can be added to exciting features to benefit businesses.
AI has taken smart technology to the next level of innovation, unfolding prospects for different industries. Further, it is expected to reach the human intelligence.
Hence, development companies are endeavoring to explore and implement its capabilities to meet advanced necessities of human and organization.
In AI, if we talk about achievement, we see biometric intelligence and autopilots for self-driving cars. For such artificial intelligence development projects, different coding language is required.
Now the question is, which programming language can help to inculcate the insence of AI and how it can be leveraged to add profitability?
For this, you will also need good machine learning and deep learning libraries. The major areas to focus are good runtime, performance , good tools support, and a large community of programmers with ecosystem.
It's not that Artificial Intelligence has its own set of programming language. However, the development company has been working hard to use the existing language.
The ease of learning, scalability, and adaptability has accelerated the popularity of Python, making it one of the fastest growing programming languages. Based on DRY (don't repeat yourself) and RAD (rapid application development), this language was developed in the early 1990s. Python's object-oriented design increases a programmer's productivity and enables faster development. Without implementation, it supports algorithm testing.
Hundreds of rich and extensive libraries available in Python make any type of AI project. For instance, Apache Spark MLlib is a very scalable machine learning library. It is very efficient, as it interoperates with the NumPy library in Python and R libraries.
It is regarded as the fastest computer language worldwide, with faster execution time and quick response time. This is a great language for AI programming as it allows extensive use of algorithms as well as statistical AI techniques. Apart from this, the speed factor makes it an ideal language for AI implementation.
It supports code reuse, having features like inheritance and data-hiding.
The language is compatible with 3D games' complexities. It optimizes resource management and facilitates multiplayer with networking.
The science fiction game, Doom 3, is a prefect real world example. (It uses C++ and the Unreal Engine, a suite of game development tools). Other C++ based applications include Microsoft Windows, Maya 3D software, CAD, Mozilla Firefox, and Adobe Photoshop.
Introducing ideas like dynamic typing, automatic storage management, tree data structure, self hosting, and others, this language is one of the most prominent languages and is known for unique flexibility. Symbolic expression and computing makes this language compliment AI. This means it supports programmer execution based on symbols computation.
Lisp comes as an ideal match for machine learning and inductive logic projects.
Java is a versatile programming language that strengthens apps/AI, transparency, portability, and maninatinability and matches AI requirements to the best. It facilitates better users integration, debugging ease to well support AI-based, large-scale projects.
Apart from this, Java Virtual Machine technology in Java language supports the creation of a single app version. This means the app will support all Java-based platforms.
Like Lisp, Prolog is a primary computer programming language suitable for development of programming AI. It offers a flexible and powerful framework for developers. It is used for non-numerical programming, processing of natural language, and theorem proves.
Having formal logic, this declarative is used by AI developers for high-level abstraction, pre-designed search mechanism, etc.
Published at DZone with permission of Saroj Kumar, DZone MVB. See the original article here.
Opinions expressed by DZone contributors are their own.