While many languages have a place in AI, Perl isn't commonly used due to its scripting nature. It lacks the powerful libraries and computational strengths favored for building and training complex AI models like those in Python, R, Java, or C++.
The choice of a programming language for AI depends on the specific requirements of the project, the expertise of the development team, and the trade-offs between factors such as ease of use, performance, and available resources. Some languages are more suitable than others e., Python, R, C++, Java while others are not e.g., HTML, XML, PHP.
A programming language's suitability for AI development depends on several factors. Firstly, the availability of robust libraries and frameworks dedicated to AI tasks is crucial. These tools simplify development and accelerate complex tasks. Secondly, an AI-friendly language should be easy to use and readable, facilitating experimentation and collaboration. Thirdly, performance and efficiency are paramount, particularly for computationally intensive algorithms. Lower-level languages like C++ and JIT-enabled languages like Julia are preferred for high-performance computing. Additionally, a strong community supporting the language ensures continuous development, knowledge sharing, and access to valuable resources. Integration capabilities are important to seamlessly connect AI systems with existing software and infrastructure. Scalability, parallel processing, and efficient memory management are also desirable for handling large-scale datasets. Lastly, industry adoption and ecosystem play a role in a language's suitability, as they indicate support, tools, and resources. Ultimately, the choice of a programming language for AI depends on project requirements, team expertise, and the trade-offs between factors like ease of use, performance, and available resources.
Since there are a lot of programming languages, it is easyer to answer the reverse - what languages are used for AI. AI training usually needs computing gradiants so progamming languages that autmatically compute gradiants are prefered - some examples are pytorch or tensorflow
I think there are C, C++, C# or Java because these progamming language are suitable for Windows applications and if you want to use them, you must be install compatible environments for them.
Natural Language (speech) is not used for AI research, but is ought to be.
The reason why it is not used is the 20th Century's focus on the Structuralism of F. de Saussure, and its need to fit language into a pattern or syntax. This is an unrealistic model of language: speech is not algorithmic.
The analogy is with mathematics and computation. Mathematics is the devising of numerical patterns (aka algorithms and techniques) to describe nature, whereas computation is the devising of any arbitrary algorithms.
Enguage provides this arbitrary swapping of utterances for natural language, whether it be English, Arabic or Chinese; language is socially constructed.
Não há uma linguagem de programação específica que não seja usada em IA. As várias linguagens de programação que existem podem ser aplicadas na construção de sistemas de inteligência artificial, dependendo dos requisitos e preferências do programador.