Discover the limitations of the self-consistency technique in generative AI and prompt engineering. Learn why computational intensity is a key challenge and how it impacts AI performance.
Table of Contents
Question
What could be a limitation of the Self-Consistency technique?
A. It reduces the variety of answers.
B. It may lead to generating irrelevant responses.
C. It always provides the fastest response.
D. It can be computationally intensive.
Answer
A. It reduces the variety of answers.
Explanation
Correct. By focusing on coherence, it may limit the diversity of responses.
The self-consistency technique in generative AI enhances accuracy by generating multiple reasoning paths for a given prompt and selecting the most consistent response. While this method improves reliability and reduces errors, it comes with notable limitations:
Computational Intensity
The self-consistency approach requires generating multiple independent responses for the same prompt, which significantly increases computational demands. Each iteration involves sampling diverse reasoning paths, aggregating them, and determining the most consistent answer. This process consumes more time and resources compared to simpler methods like greedy decoding or single-pass generation.
For complex tasks, such as arithmetic or commonsense reasoning, the computational cost rises further as more reasoning paths are sampled to ensure accuracy.
Other Limitations (Not Relevant to Question)
While not directly related to this question, other challenges of self-consistency include sensitivity to prompt quality, large data requirements, and diminishing returns with excessive sampling.
Why Other Options Are Incorrect
- A. It reduces the variety of answers: Self-consistency does not inherently limit variety; instead, it leverages diversity in reasoning paths to select the most consistent answer. This increases reliability rather than reducing variety.
- B. It may lead to generating irrelevant responses: Self-consistency minimizes irrelevant outputs by focusing on consistent answers across multiple generations.
- C. It always provides the fastest response: This is incorrect because self-consistency is slower due to its computational nature, as explained above.
In summary, while self-consistency is a powerful technique for improving AI accuracy, its primary limitation lies in its computational intensity, making D the correct answer.
Udemy Generative AI & Prompt Engineering certification exam assessment practice question and answer (Q&A) dump including multiple choice questions (MCQ) and objective type questions, with detail explanation and reference available free, helpful to pass the Udemy Generative AI & Prompt Engineering exam and earn Udemy Generative AI & Prompt Engineering certification.