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Updated D-GAI-F-01 Latest Exam Registration, New D-GAI-F-01 Test Camp
The goal of D-GAI-F-01 preparation material is to help applicants prepare for the Dell GenAI Foundations Achievement certification exam by providing them with the Actual D-GAI-F-01 Exam Questions they need to pass the exam. This Dell GenAI Foundations Achievement (D-GAI-F-01) study material is in the form of practice tests and D-GAI-F-01 PDF that thoroughly covers the content of the test.
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EMC Dell GenAI Foundations Achievement Sample Questions (Q11-Q16):
NEW QUESTION # 11
What is the purpose of fine-tuning in the generative Al lifecycle?
- A. To feed the model a large volume of data from a wide variety of subjects
- B. To customize the model for a specific task by feeding it task-specific content
- C. To randomize all the statistical weights of the neural network
- D. To put text into a prompt to interact with the cloud-based Al system
Answer: B
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.
NEW QUESTION # 12
What are the potential impacts of Al in business? (Select two)
- A. Improving operational efficiency and enhancing customer experiences
- B. Reducing production and operating costs
- C. Limiting the use of data analytics
- D. Increasing the need for human intervention
Answer: A,B
Explanation:
Reducing Costs: AI can automate repetitive and time-consuming tasks, leading to significant cost savings in production and operations. By optimizing resource allocation and minimizing errors, businesses can lower their operating expenses.
NEW QUESTION # 13
You are tasked with creating a model that uses a competitive setting between two neural networks to create new data.
Which model would you use?
- A. Variational Autoencoders (VAEs)
- B. Generative Adversarial Networks (GANs)
- C. Transformers
- D. Feedforward Neural Networks
Answer: B
Explanation:
Generative Adversarial Networks (GANs) are a class of machine learning frameworks designed by Ian Goodfellow and his colleagues in 2014. GANs consist of two neural networks, the generator and the discriminator, which are trained simultaneously through a competitive process. The generator creates new data instances, while the discriminator evaluates them against real data, effectively learning to generate new content that is indistinguishable from genuine data.
The generator's goal is to produce data that is so similar to the real data that the discriminator cannot tell the difference, while the discriminator's goal is to correctly identify whether the data it reviews is real (from the actual dataset) or fake (created by the generator). This competitive process results in the generator creating highly realistic data.
The Official Dell GenAI Foundations Achievement document likely includes information on GANs, as they are a significant concept in the field of artificial intelligence and machine learning, particularly in the context of generative AI12. GANs have a wide range of applications, including image generation, style transfer, data augmentation, and more.
Feedforward Neural Networks (Option OA) are basic neural networks where connections between the nodes do not form a cycle. Variational Autoencoders (VAEs) (Option OB) are a type of autoencoder that provides a probabilistic manner for describing an observation in latent space. Transformers (Option OD) are a type of model that uses self-attention mechanisms and is widely used in natural language processing tasks. While these are all important models in AI, they do not use a competitive setting between two networks to create new data, making Option OC the correct answer.
NEW QUESTION # 14
A company is considering using Generative Al in its operations.
Which of the following is a benefit of using Generative Al?
- A. Decreased innovation
- B. Increased manual labor
- C. Higher operational costs
- D. Enhanced customer experience
Answer: D
Explanation:
Generative AI has the potential to significantly enhance the customer experience. It can be used to personalize interactions, automate responses, and provide more engaging content, which can lead to a more satisfying and tailored experience for customers.
The Official Dell GenAI Foundations Achievement document would likely highlight the importance of customer experience in the context of AI. It would discuss how Generative AI can be leveraged to create more personalized and engaging interactions, which are key components of a positive customer experience1.
Additionally, Generative AI can help businesses understand and predict customer needs and preferences, enabling them to offer better service and support23.
Decreased innovation (Option OA), higher operational costs (Option OB), and increased manual labor (Option OD) are not benefits of using Generative AI. In fact, Generative AI is often associated with fostering greater innovation, reducing operational costs, and automating tasks that would otherwise require manual effort.
Therefore, the correct answer is C. Enhanced customer experience, as it is a recognized benefit of implementing Generative AI in business operations.
NEW QUESTION # 15
A tech startup is developing a chatbot that can generate human-like text to interact with its users.
What is the primary function of the Large Language Models (LLMs) they might use?
- A. To encrypt information
- B. To store data
- C. To manage databases
- D. To generate human-like text
Answer: D
Explanation:
Large Language Models (LLMs), such as GPT-4, are designed to understand and generate human-like text.
They are trained on vast amounts of text data, which enables them to produce responses that can mimic human writing styles and conversation patterns. The primary function of LLMs in the context of a chatbot is to interact with users by generating text that is coherent, contextually relevant, and engaging.
The Dell GenAI Foundations Achievement document outlines the role of LLMs in generative AI, which includes their ability to generate text that resembles human language1. This is essential for chatbots, as they are intended to provide a conversational experience that is as natural and seamless as possible.
Storing data (Option OA), encrypting information (Option OB), and managing databases (Option OD) are not the primary functions of LLMs. While LLMs may be used in conjunction with systems that perform these tasks, their core capability lies in text generation, making Option OC the correct answer.
NEW QUESTION # 16
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