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Question 32 - D-GAI-F-01 discussion

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A company is planning its resources for the generative Al lifecycle.

Which phase requires the largest amount of resources?

A.
Deployment
Answers
A.
Deployment
B.
Inferencing
Answers
B.
Inferencing
C.
Fine-tuning
Answers
C.
Fine-tuning
D.
Training
Answers
D.
Training
Suggested answer: D

Explanation:

The training phase of the generative AI lifecycle typically requires the largest amount of resources. This is because training involves processing large datasets to create models that can generate new data or predictions. It requires significant computational power and time, especially for complex models such as deep learning neural networks. The resources needed include data storage, processing power (often using GPUs or specialized hardware), and the time required for the model to learn from the data.

In contrast, deployment involves implementing the model into a production environment, which, while important, often does not require as much resource intensity as the training phase. Inferencing is the process where the trained model makes predictions, which does require resources but not to the extent of the training phase. Fine-tuning is a process of adjusting a pre-trained model to a specific task, which also uses fewer resources compared to the initial training phase.

The Official Dell GenAI Foundations Achievement document outlines the importance of understanding the concepts of artificial intelligence, machine learning, and deep learning, as well as the scope and need of AI in business today, which includes knowledge of the generative AI lifecycle1.

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asked 16/09/2024
Larry Warren
31 questions
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