Fdaytalk Homework Help: Questions and Answers: Which of the following is a use case for traditional Al?
Answer:
This question is about traditional AI. To identify a use case for traditional AI, we first need to understand what exactly ‘traditional AI’ refers to:
Traditional AI generally involves rule-based systems, expert systems, and classical machine learning algorithms. It doesn’t usually include more advanced techniques like deep learning or neural networks.
Given Options: Step-by-Step Solution:
a) Generating art from text descriptions:
- Generating art from text descriptions is a use case associated with generative AI, specifically involving models like GANs (Generative Adversarial Networks) or advanced models like DALL-E. So, this is not a use case for traditional AI.
b) Predicting stock market trends:
- Predicting stock market trends involves analyzing historical data, patterns, and trends to forecast future market movements. This is a classic example of traditional AI applications, which use machine learning algorithms and statistical methods.
c) Translating between languages:
- Translating between languages is typically done using neural networks and modern machine learning techniques, such as those used in Google’s Neural Machine Translation (GNMT) system. While early translation systems were rule-based (traditional AI), modern systems use deep learning. We should that note that older systems were traditional AI, but current systems predominantly use advanced AI.
d) Creating realistic facial images:
- Creating realistic facial images is another task associated with generative AI, using techniques such as GANs to produce high-quality, realistic images from latent space representations. This is not a use case for traditional AI.
Based on the above analysis, the correct options is:
Correct answer: Option B
Among the given options, predicting stock market trends (Option b) is a use case for traditional AI, utilizing established statistical and machine learning techniques to analyze and predict data patterns.
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