Question

Give any two examples of each of the following with respect to evaluation of AI development platforms:
(a) Open Languages
(b) Productivity Enhancing Capabilities

Hint:

Tip: Look for open language support + built-in tools for faster, easier AI development.

Answer 1

When evaluating AI development platforms, it is important to check if they support open languages and offer features that enhance developer productivity.
(a) Open Languages:
Examples of popular open languages used in AI development include:
1. Python — An open-source, versatile language widely used for machine learning, deep learning, and data science tasks.
2. R — An open-source statistical computing language often used for data analysis and visualization in AI projects.
(b) Productivity Enhancing Capabilities:
These are features or tools that help developers build and deploy AI solutions more efficiently. Examples include:
1. Integrated Development Environment (IDE) Support — Built-in editors, debuggers, and testing tools that streamline coding.
For example: Jupyter Notebooks, PyCharm for Python.
2. Pre-built Libraries and Frameworks — Availability of ready-made packages such as TensorFlow, Scikit-learn, or Keras, which save time and effort.
Having open language support and productivity features makes an AI platform more flexible and user-friendly for developers.