TOP PROGRAMMING LANGUAGES IN TREND FOR AI PROJECTS IN 2020
AI programming is an elevation of technology that has brought efficiency and optimum benefits to different company’s operations and people’s lives. AI has brought another level of smart technology to different industries and the prospects of its potential still grow with the expectation that it would reach human intelligence. This is because developers are willing to explore, experiment, and implement their capabilities to satisfy more of the human and organization necessities. After all, necessity is the mother of invention.
Therefore, here is the list of top 5 programming languages that are in trend for AI developments in 2020.
Python is an Interpreted language which in lay man’s terms means that it does not need to be compiled into machine language instruction before execution and can be used by the developer directly to run the program. This makes it comprehensive enough for the language to be interpreted by an emulator or a virtual machine on top of the native machine language which is what the hardware understands.
Python offers the least code among others and is in fact 1/5 the number compared to other OOP languages. No wonder it is one of the most popular in the market today.
Python has Prebuilt Libraries like Numpy for scientific computation, Scipy for advanced computing, and Pybrain for machine learning (Python Machine Learning) making it one of the best languages For AI.
R is a multi-paradigm language that can be called a procedural one, much like Python is. It can also support object-oriented programming, but it is not known for that feature as much as Python is.
R is considered to be a statistical workhorse, more so than Python. Once you start learning, you will understand that statistics form the base of machine learning and AI too. This means that you will need something which can suit your needs, and R is just that. R is considered to be similar to SAS and SPSS, which are other common statistical software. It is well suited for data analysis, visualization, and statistics in general. However, it is less flexible compared to Python but is more specialized too.
R is an open-source language too. This does not simply mean that it is free to use, for you – it also implies that you will have a lot of support when you start to use it. R has a vast community of users, so there is no dearth of help from expert practitioners if you ever need any.
One of the best things about Java is Java Virtual Machine Technology. This technology allows developers to build a single app version that will run on all Java-enabled computing platforms. Major strengths of this programming language are as following: maintainability; portability; transparency.
AI is closely connected with search algorithms, genetic programming, and the use of artificial neural networks. Java in the artificial intelligence sphere may be more than useful. Programming AI in Java has many benefits: easy use, debugging ease, simplified work with large-scale projects, facilitated visualization, better user interaction. Another reason for programming AI in Java is the incorporation of Swing and SWT (the Standard Widget Toolkit). These features make graphics and interfaces look appealing and sophisticated.
Another reason for using Java in AI programming is the vast amount of tutorials on the Internet. Just type “how to program artificial intelligence in Java” and you’ll get a lot of pages to choose from. Java is versatile. It’s used for making multi-robot systems, sensor networks, and machine learning suites.
Just like Java, Scala belongs to the JVM family. Scala is a fairly new language in the AI space but it’s finding quite a bit of recognition recently in many corporations and startups.
It has a lot to offer in terms of convenience which is why developers enjoy working with it. Also, ScalaNLP, DeepLearning4j, etc are all tools and libraries that make the AI development process a bit easier with Scala. It’s good for projects that need scalability and combines the strengths of Functional and Imperative programming models to act as a powerful tool that helps build highly concurrent applications while reaping the benefits of an OO approach at the same time.
Scala provides good concurrency support which helps with projects involving real-time parallelized analytics. It has a good open source community when it comes to statistical learning, information theory, and Artificial Intelligence in general.
The most loved language of all is Rust, an open-source programming language that was hatched by tech pioneers at Mozilla in 2010.
In fact, Rust has been voted the most-loved language for the past four years in Stack Overflow’s annual developer surveys as solves pain points present in many other languages, providing a solid step forward with a limited number of downsides.
Rust concepts are also being used in Microsoft’s recently open-sourced Project Verona, an experimental language for safe infrastructure programming that could help Microsoft securely retain legacy C and C# code.
Mozilla Research describes Rust as a “systems programming language that focuses on speed, memory safety, and parallelism”.