What are the three key patrons involved in supporting the successful progress and formation of any Al-based application?

Customer facing teams, executive team, and data science team

Customer facing teams, executive team, and facilities team

Marketing team, executive team, and data science team

Customer facing teams, HR team, and data science team

Customer facing teams, executive team, and data science team

What is the difference between supervised and unsupervised learning in the context of training Large Language Models (LLMs)?

Supervised learning uses labeled data to teach the Al system what output is expected, while unsupervised learning feeds a large corpus of raw data into the Al system, which determines the appropriate weights in its neural network.

Supervised learning feeds a large corpus of raw data into the Al system, while unsupervised learning uses labeled data to teach the Al system what output is expected.

Supervised learning is common for fine tuning and customization, while unsupervised learning is common for base model training.

Supervised learning uses labeled data to teach the Al system what output is expected, while unsupervised learning feeds a large corpus of raw data into the Al system, which determines the appropriate weights in its neural network.

Supervised learning is common for base model training, while unsupervised learning is common for fine tuning and customization.

Why is diversity important in Al training data?

To ensure the model can generalize across different scenarios

To make Al models cheaper to develop

To reduce the storage requirements for data

To ensure the model can generalize across different scenarios

To increase the model's speed of computation

What is the first step an organization must take towards developing an Al-based application?

Address ethical and legal issues.

What is the primary purpose of fine-tuning in the lifecycle of a Large Language Model (LLM)?

To customize the model for a specific task by feeding it task-specific content

To randomize all the statistical weights of the neural network

To customize the model for a specific task by feeding it task-specific content

To feed the model a large volume of data from a wide variety of subjects

To put text into a prompt to interact with the cloud-based Al system

Why should artificial intelligence developers always take inputs from diverse sources?

To cover all possible cases that the model should handle

To investigate the model requirements properly

To perform exploratory data analysis

To determine where and how the dataset is produced

To cover all possible cases that the model should handle

What is the purpose of the explainer loops in the context of Al models?

They are used to provide insights into the model's reasoning, allowing users and developers to understand why a model makes certain predictions or decisions.

They are used to increase the complexity of the Al models.

They are used to provide insights into the model's reasoning, allowing users and developers to understand why a model makes certain predictions or decisions.

They are used to reduce the accuracy of the Al models.

They are used to increase the bias in the Al models.

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

To customize the model for a specific task by feeding it task-specific content

To put text into a prompt to interact with the cloud-based Al system

To randomize all the statistical weights of the neural network

To customize the model for a specific task by feeding it task-specific content

To feed the model a large volume of data from a wide variety of subjects

What is one of the objectives of Al in the context of digital transformation?

To become essential to the success of the digital economy

To reduce the need for Internet connectivity

To replace all human tasks with automation

To eliminate the need for data privacy

What is Transfer Learning in the context of Language Model (LLM) customization?

It is a type of model training that occurs when you take a base LLM that has been trained and then train it on a different task while using all its existing base weights.

It is where you can adjust prompts to shape the model's output without modifying its underlying weights.

It is a process where the model is additionally trained on something like human feedback.

It is a type of model training that occurs when you take a base LLM that has been trained and then train it on a different task while using all its existing base weights.

It is where purposefully malicious inputs are provided to the model to make the model more resistant to adversarial attacks.

What is the significance of parameters in Large Language Models (LLMs)?

Parameters are statistical weights inside of the neural network of LLMs.

Parameters are used to parse image, audio, and video data in LLMs.

Parameters are used to decrease the size of the LLMs.

Parameters are used to increase the size of the LLMs.

Parameters are statistical weights inside of the neural network of LLMs.

What is the primary function of Large Language Models (LLMs) in the context of Natural Language Processing?

LLMs receive input in human language and produce output in human language.

LLMs are used to shrink the size of the neural network.

LLMs are used to increase the size of the neural network.

LLMs are used to parse image, audio, and video data.

What is the primary purpose oi inferencing in the lifecycle of a Large Language Model (LLM)?

To use the model in a production, research, or test environment

To customize the model for a specific task by feeding it task-specific content

To feed the model a large volume of data from a wide variety of subjects

To use the model in a production, research, or test environment

To randomize all the statistical weights of the neural networks

What strategy can an organization implement to mitigate bias and address a lack of diversity in technology?

Partner with nonprofit organizations, customers, and peer companies on coalitions, advocacy groups, and public policy initiatives.

Limit partnerships with nonprofits and nongovernmental organizations.

Partner with nonprofit organizations, customers, and peer companies on coalitions, advocacy groups, and public policy initiatives.

Reduce diversity across technology teams and roles.

Ignore the issue and hope it resolves itself over time.

What is P-Tuning in LLM?

Adjusting prompts to shape the model's output without altering its core structure

Preventing a model from generating malicious content

Personalizing the training of a model to produce biased outputs

Punishing the model for generating incorrect answers

What role does human feedback play in Reinforcement Learning for LLMs?

It rewards good output and penalizes bad output to improve the model.

It is used to provide real-time corrections to the model's output.

It helps in identifying the model's architecture for optimization.

It assists in the physical hardware improvement of the model.

It rewards good output and penalizes bad output to improve the model.

What are the potential impacts of Al in business? (Select two)

Reducing production and operating costs

Improving operational efficiency and enhancing customer experiences

Limiting the use of data analytics

Increasing the need for human intervention

Reducing production and operating costs

Improving operational efficiency and enhancing customer experiences

What is the purpose of adversarial training in the lifecycle of a Large Language Model (LLM)?

To make the model more resistant to attacks like prompt injections when it is deployed in production

To feed the model a large volume of data from a wide variety of subjects

To customize the model for a specific task by feeding it task-specific content

To randomize all the statistical weights of the neural network

What is the role of a decoder in a GPT model?

It takes the input and determines the appropriate output.

It is used to fine-tune the model.

It takes the output and determines the input.

It takes the input and determines the appropriate output.

It is used to deploy the model in a production or test environment.

What are the enablers that contribute towards the growth of artificial intelligence and its related technologies?

The abundance of data, lower cost high-performance compute, and improved algorithms

The introduction of 5G networks and the expansion of internet service provider coverage

The development of blockchain technology and quantum computing

The abundance of data, lower cost high-performance compute, and improved algorithms

The creation of the Internet and the widespread use of cloud computing

What is feature-based transfer learning?

Selecting specific features of a model to keep while removing others

Transferring the learning process to a new model

Training a model on entirely new features

Enhancing the model's features with real-time data

Selecting specific features of a model to keep while removing others

What strategy can an Al-based company use to develop a continuous improvement culture?

Focus on the improvement of human-driven processes.

Limit the involvement of humans in decision-making processes.

Focus on the improvement of human-driven processes.

Discourage the use of Al in education systems.

Build a small Al community with people of similar backgrounds.

What are common misconceptions people have about Al? (Select two)

Al is not prone to generate errors.

What is a principle that guides organizations, government, and developers towards the ethical use of Al?

Al models must ensure data privacy and confidentiality.

Only regulatory agencies should be held accountable for the accuracy, fairness, and use of Al models

The value of Al models must only be measured in financial gain.

Al models must ensure data privacy and confidentiality.

Al models must always agree with the user's point of view.

A company wants to use Al to improve its customer service by generating personalized responses to customer inquiries.Which of the following is a way Generative Al can be used to improve customer experience?

By providing personalized and timely responses through chatbots

By generating new product designs

By providing personalized and timely responses through chatbots

A company is considering using deep neural networks in its LLMs.What is one of the key benefits of doing so?

They can handle more complicated problems

A healthcare company wants to use Al to assist in diagnosing diseases by analyzing medical images.Which of the following is an application of Generative Al in this field?

Analyzing medical images for diagnosis

A team of researchers is developing a neural network where one part of the network compresses input data.What is this part of the network called?

Discerner of real from fake data

DELL D-GAI-F-01 Practice Test 1 - Free Online Exam Prep & Questions

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What is Artificial Narrow Intelligence (ANI)?

Al systems that can perform any task autonomously

Al systems that can process beyond human capabilities

Al systems that can think and make decisions like humans

Al systems that can perform a specific task autonomously

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