Introduction to Generative AI: Quiz Answers

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Course Link:  Introduction to Generative AI

Introduction to Generative AI: Quiz Answers

Question 1)

What is Generative AI?:

• Generative AI is a type of artificial intelligence (AI) that can create new content, such as discrete numbers, classes, and probabilities. It does this by learning from existing data and then using that knowledge to generate new and unique outputs.

• Generative AI is a type of artificial intelligence (AI) that can only create new content, such as text, images, audio, and video by learning from new data and then using that knowledge to predict a classification output.

• Generative AI is a type of artificial intelligence (AI) that can create new content, such as text, images, audio, and video. It does this by learning from existing data and then using that knowledge to generate new and unique outputs.

• Generative AI is a type of artificial intelligence (AI) that can only create new content, such as text, images, audio, and video by learning from new data and then using that knowledge to predict a discrete, supervised learning output.

Question 2)

What is an example of both a generative AI model and a discriminative AI model?

• A generative AI model could be trained on a dataset of images of cats and then used to cluster images of cats. A discriminative AI model could be trained on a dataset of images of cats and dogs and then used to predict as either cats or dogs.

• A generative AI model could be trained on a dataset of images of cats and then used to classify new images of cats. A discriminative AI model could be trained on a dataset of images of cats and dogs and then used to predict new images as either cats or dogs.

• A generative AI model could be trained on a dataset of images of cats and then used to generate new images of cats. A discriminative AI model could be trained on a dataset of images of cats and dogs and then used to classify new images as either cats or dogs.

• A generative AI model does not need to be trained on a dataset of images of cats and then used to generate new images of cats, because the images were already generated by using AI. A discriminative AI model could be trained on a dataset of images of cats and dogs and then used to classify new images as either cats or dogs.

Question 3)

What are foundation models in Generative AI?

• A foundation model is a large AI model post-trained on a vast quantity of data that was "designed to be adapted” (or fine-tuned) to a wide range of downstream tasks, such as sentiment analysis, image captioning, and object recognition.

• A foundation model is a large AI model pretrained on a vast quantity of data that was "designed to be adapted” (or fine-tuned) to a wide range of upstream tasks, such as sentiment analysis, image captioning, and object recognition.

• A foundation model is a small AI model pretrained on a small quantity of data that was "designed to be adapted” (or fine-tuned) to a wide range of downstream tasks, such as sentiment analysis, image captioning, and object recognition.

• A foundation model is a large AI model pretrained on a vast quantity of data that was "designed to be adapted” (or fine-tuned) to a wide range of downstream tasks, such as sentiment analysis, image captioning, and object recognition.

• A foundation model is a large AI model both post and pre-trained on a vast quantity of data that was "designed to be adapted” (or fine-tuned) to a wide range of downstream tasks, such as sentiment analysis, image captioning, and object recognition.

Question 4)

Hallucinations are words or phrases that are generated by the model that are often nonsensical or grammatically incorrect. What are some factors that can cause hallucinations? Select three options.

• The model is trained on noisy or dirty data.

• The model is trained on too much data.

• The model is not given enough context.

• The model is not trained on enough data

Question 5)

What is a prompt?

• A prompt is a short piece of text that is given to the small language model (SLM) as input, and it can be used to control the output of the model in many ways.

• A prompt is a short piece of text that is given to the arge language model as input, and it can be used to control the input of the model in many ways.

• A prompt is a short piece of code that is given to the large language model as input, and it can be used to control the output of the model in many ways.

• A prompt is a short piece of text that is given to the large language model as input, and it can be used to control the output of the model in many ways.

• A prompt is a long piece of text that is given to the large language model as input, and it cannot be used to control the output of the model.