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Knowledge
Generative AI represents a transformative technology that can create text, images, music, and more using trained data. Its applications span various fields like education, art, healthcare, and business, showcasing how it reshapes creative processes and decision-making. The chapter emphasizes real-world examples and tools that illustrate the practical implications and efficiencies brought by Generative AI.
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Sections
References
ch12.pdfClass Notes
Memorization
What we have learnt
- Generative AI creates new c...
- It is used in education, ar...
- Tools like ChatGPT, DALL·E,...
Final Test
Revision Tests
What we have learnt
- Generative AI creates new content from existing data.
- It is used in education, art, music, healthcare, business, and more.
- Tools like ChatGPT, DALL·E, and GitHub Copilot are examples of Generative AI in action.
- It saves time, boosts creativity, and improves productivity.
Key Concepts
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Term: Generative AI
Definition: AI models capable of generating new content based on trained data.
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Term: Generative Adversarial Networks (GANs)
Definition: A class of machine learning frameworks involving two neural networks contesting with each other to improve content generation.
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Term: Transformers
Definition: A type of model architecture used in processing sequential data and has become foundational in understanding natural language.
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Term: Deep Learning
Definition: A subset of machine learning using neural networks with many layers to extract features from data for complex tasks.