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Question 14 - D-GAI-F-01 discussion

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What is the purpose of fine-tuning in the generative Al lifecycle?

A.
To put text into a prompt to interact with the cloud-based Al system
Answers
A.
To put text into a prompt to interact with the cloud-based Al system
B.
To randomize all the statistical weights of the neural network
Answers
B.
To randomize all the statistical weights of the neural network
C.
To customize the model for a specific task by feeding it task-specific content
Answers
C.
To customize the model for a specific task by feeding it task-specific content
D.
To feed the model a large volume of data from a wide variety of subjects
Answers
D.
To feed the model a large volume of data from a wide variety of subjects
Suggested answer: C

Explanation:

Customization: Fine-tuning involves adjusting a pretrained model on a smaller dataset relevant to a specific task, enhancing its performance for that particular application.

Process: This process refines the model's weights and parameters, allowing it to adapt from its general knowledge base to specific nuances and requirements of the new task.

Applications: Fine-tuning is widely used in various domains, such as customizing a language model for customer service chatbots or adapting an image recognition model for medical imaging analysis.

asked 16/09/2024
J.L.M. van Loo
48 questions
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