COURSE 3 – GENERATIVE AI: INTRODUCTION AND APPLICATIONS
Module 1: Introduction and Capabilities of Generative AI
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INTRODUCTION – Introduction and Capabilities of Generative AI
In this module, you’ll delve into the core principles of generative artificial intelligence (AI) and explore its distinctions from discriminative AI. Through this exploration, you’ll uncover the diverse applications of generative AI across text, image, code, speech, and video generation, as well as its role in data augmentation. Understanding these fundamentals will provide a solid foundation for grasping the potential and versatility of generative AI technologies.
By the end of this module, you’ll not only comprehend the essential concepts of generative AI but also recognize its practical implications across various domains. From its ability to create diverse forms of media to its utility in enhancing datasets through augmentation, generative AI showcases a breadth of possibilities that can revolutionize industries and innovation.
Learning Objectives
- Demonstrate use cases of generative AI for text, image, and code generation
- Describe generative AI and its evolution
- Contrast generative AI with discriminative AI
- Describe common capabilities of generative AI for the generation of text, image, audio, video, virtual worlds, code, and data
- Demonstrate use cases of generative AI for text generation.
PRACTICE QUIZ: GENERATIVE AI AND ITS CAPABILITIES
1. Generative AI models can _________ the training data to create unique content.
- Draw conclusions from
- Identify patterns and classify
- Differentiate between
- Learn from (CORRECT)
Correct! Generative AI applications can learn from the training data to create unique content.
2. What does generative AI do differently than discriminative AI?
- Mimics the human ability to analyze data
- Mimics the human ability to classify data
- Mimics the human ability to predict data
- Mimics the human ability to create data (CORRECT)
Correct! Generative AI mimics the human ability to create data, which differentiates it from discriminative AI.
3. What type of generative AI capability does a large language model primarily exhibit?
- Audio generation
- Text generation (CORRECT)
- Data augmentation
- Image generation
Correct! A large language model primarily exhibits the text generation capabilities of Generative AI, which include the ability to generate clear, lucid, and contextually relevant textual responses.
GRADED QUIZ: INTRODUCTION AND CAPABILITIES OF GENERATIVE AI
1. Using a generative AI tool, Emily wants to create an image of a zebra-striped cat with a purple hat. Identify the best prompt for this task.
- What’s the difference between a zebra and a cat?
- Find a zebra-striped cat that wears a purple hat.
- List cat breeds that look like zebras or have stripes.
- Draw an image of a zebra-striped cat with a purple hat. (CORRECT)
Correct! Giving the generative AI image generation tool a clear prompt can help achieve the desired output.
2. Tiana is designing a game and decides to create one avatar with specific personality traits. What type of generative AI capability is Tiana using?
- Ability to augment data
- Ability to generate dynamic films
- Ability to synthesize images
- Ability to create virtual worlds (CORRECT)
Correct! A powerful capability of generative AI models is to create highly realistic and complex virtual worlds, including avatars.
3. A metaverse platform with generative AI capabilities will allow you to access _______________, which is not possible with other generative AI tools.
- Synthetic images
- Augmented data sets
- Clear and contextually relevant text
- Virtual avatars (CORRECT)
Correct! Metaverse platforms allow users to access virtual environments, using personalized representations called “avatars.”
4. What input data does VideoGPT best respond to?
- Video prompts
- Image prompts
- Text prompts (CORRECT)
- AI-generated code
Correct! AI model VideoGPT follows textual prompts users provide to generate new videos.
CONCLUSION – Introduction and Capabilities of Generative AI
In conclusion, this module serves as a gateway to understanding the fundamental principles and diverse applications of generative artificial intelligence (AI). By distinguishing it from discriminative AI and exploring its capabilities in text, image, code, speech, and video generation, as well as data augmentation, learners gain insight into the vast potential of this technology.
With a solid grasp of these concepts, individuals are equipped to harness the power of generative AI to innovate and revolutionize industries across the board. As the field continues to evolve, the knowledge gained from this module will serve as a valuable foundation for further exploration and advancement in the exciting realm of generative AI.
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