Which programming languages are commonly used with IBM Watson services?

Which programming languages are commonly used with IBM Watson services?

• A. C++ and Ruby
• B. Python, Java, and Node.js
• C. SML and Assembly
• D. HTML and CSS

Answer: (B)

IBM Watson services are designed to integrate easily with various programming languages, enabling developers to harness the capabilities of artificial intelligence in their applications. Python, Java, and Node.js stand out as the most common languages used with IBM Watson because these languages provide robust libraries and frameworks specifically aimed at simplifying interaction with Watson's APIs. Python is particularly popular for its simplicity and the large ecosystem of data science and machine learning libraries, making it ideal for tasks such as natural language processing, data analysis, and building AI models. Java, on the other hand, is widely used in enterprise environments, offering performance and scalability, which are important for integrating AI into larger systems. Node.js provides an efficient way to build scalable network applications, which is beneficial for real-time data processing and handling interactive applications powered by Watson services. In contrast, the other choices consist of programming languages or technologies that do not commonly integrate with IBM Watson. C++ and Ruby are less prevalent in AI application development with Watson, while SML and Assembly are more niche and low-level programming languages not typically used in the context of AI services. HTML and CSS are web development languages focused on structure and presentation, not on server-side operations or AI functionalities. Hence, the selection of Python, Java, and Node.js

IBM Watson services are designed to integrate easily with various programming languages, enabling developers to harness the capabilities of artificial intelligence in their applications. Python, Java, and Node.js stand out as the most common languages used with IBM Watson because these languages provide robust libraries and frameworks specifically aimed at simplifying interaction with Watson's APIs.

Python is particularly popular for its simplicity and the large ecosystem of data science and machine learning libraries, making it ideal for tasks such as natural language processing, data analysis, and building AI models. Java, on the other hand, is widely used in enterprise environments, offering performance and scalability, which are important for integrating AI into larger systems. Node.js provides an efficient way to build scalable network applications, which is beneficial for real-time data processing and handling interactive applications powered by Watson services.

In contrast, the other choices consist of programming languages or technologies that do not commonly integrate with IBM Watson. C++ and Ruby are less prevalent in AI application development with Watson, while SML and Assembly are more niche and low-level programming languages not typically used in the context of AI services. HTML and CSS are web development languages focused on structure and presentation, not on server-side operations or AI functionalities. Hence, the selection of Python, Java, and Node.js