Artificial intelligence (AI), a fast-developing area, has recently attracted considerable attention. Programmers use several programming languages, which give the essential frameworks and tools to complete AI tasks. As an alternative to more antiquated languages like FORTRAN, BASIC, or COBOL, I will explore two programming languages frequently used in AI in this response and emphasize their applicability.

Programming languages used to accomplish AI

One of the most popular programming languages for usage in AI applications is Python.

It provides several AI-specific libraries and frameworks, including TensorFlow and PyTorch. Python is popular in AI development due to its simplicity of use and the availability of libraries that make difficult AI tasks (Gunning & Aha,2019). Python's clear syntax and extensive ecosystem of AI-focused libraries make it ideal for quick experimentation and prototyping, which speeds up the development process.

R is yet another popular programming language in AI. R excels at statistical analysis and data visualization, whereas Python shines in general-purpose programming and machine learning (Alvarez-Dionisi et al.,2019). One of R's key strengths is its extensive collection of statistical libraries, including caret and dplyr, which make complex data processing and modeling possible. The authors emphasized R's strengths for statistical modeling and exploratory data analysis, allowing researchers to conclude large datasets quickly.

Comparison with the older languages

Python and R offer several benefits in AI compared to more antiquated languages like FORTRAN, BASIC, or COBOL. First, developers can use pre-existing tools and algorithms by utilizing the large libraries and frameworks both Python and R provide that are designed expressly for AI applications (Ribeiro et al.,2021). It drastically reduces the time and effort needed to create and execute AI solutions. Additionally, developers may readily obtain resources, documentation, and support from other professionals because of Python and R's larger and more active communities.

Conclusion

In conclusion, Python and R have become widely used programming languages in artificial intelligence because of their community support, libraries, and ease of use. These languages give programmers the frameworks and tools to implement AI algorithms effectively. The readability, community support, and accessibility of Python and R are significantly better than those of more antiquated languages like FORTRAN, BASIC, or COBOL. They are the preferred languages for researchers and professionals due to their adaptability to AI tasks.

References