GenAI vs Traditional ML model question

[paul10101]

Category: AIF – Fundamentals of AI and ML

question on Set 1 questions- pick either Traditional or GenAI for each scenario

A technology company is working on multiple cutting-edge projects that require various machine learning models to solve distinct challenges. These projects cover areas such as natural language processing, customer behavior prediction, and content creation for marketing. The team must decide which type of machine learning model best fits each specific project.

For each of the following use cases, choose the most appropriate machine learning model type from the list provided. Some model types may be used more than once.

Identify the sentiment behind customer feedback and social media posts. (Correct answer: Traditional ML model)

My question: customer feedback and Social media posts are unstructured data, are they not? so would this not be a better task for GenAI?

• This discussion was modified 1 month, 4 weeks ago by  paul10101.

[Irene-TutorialsDojo]

Hello paul10101,

That’s a great question, and the distinction can definitely be confusing at first.

While customer feedback and social media posts are indeed unstructured data, the deciding factor in this scenario is the task’s goal, not the data format. Identifying sentiment is a classification problem, where the model assigns predefined labels such as positive, negative, or neutral to existing text. Traditional machine learning models are well suited for this type of analysis and have long been used for sentiment detection by transforming text into numerical features and applying supervised learning techniques.

Generative AI, on the other hand, is primarily designed to create new content rather than label or categorize existing data. Since this use case focuses on analyzing and classifying sentiment rather than generating text, Traditional ML model remains the correct and exam-aligned answer.

Best,

Irene @ Tutorials Dojo