CBSE Class 9 AI (Artificial Intelligence) | 9. Introduction to Generative AI by Abraham | Learn Smarter
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9. Introduction to Generative AI

Generative AI is a rapidly developing area of artificial intelligence that enables machines to create new content such as text, images, and music, similar to human creativity. It operates using advanced models like Generative Adversarial Networks (GANs) and transformers, showcasing significant applications across various sectors. While offering creativity boosts and time-saving benefits, generative AI also presents risks, including potential misuse, bias, and the need for ethical considerations in its use.

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Sections

  • 9

    Introduction To Generative Ai

    Generative AI represents a significant advance in artificial intelligence, enabling machines to create new content like text, images, and music, unlike traditional AI which primarily analyzes and classifies data.

    Learning Practice

  • 9.1

    What Is Generative Ai?

    Generative AI is a branch of artificial intelligence that creates new content from learned data, such as text, images, and music.

    Learning Practice

  • 9.2

    How Does Generative Ai Work?

    Generative AI uses advanced machine learning techniques to create new content based on existing data, primarily through Generative Adversarial Networks (GANs) and Transformers.

    Learning Practice

  • 9.3

    Applications Of Generative Ai

    Generative AI is applied across various industries for tasks like creating educational content, artwork, entertainment, and business communications.

    Learning Practice

  • 9.4

    Benefits Of Generative Ai

    Generative AI offers several benefits, including enhanced creativity, time savings, increased accessibility, and cost-effectiveness.

    Learning Practice

  • 9.5

    Risks And Ethical Concerns

    Generative AI presents various risks, including fake content, plagiarism, and biases that can lead to ethical concerns.

    Learning Practice

  • 9.6

    Responsible Use Of Generative Ai

    Students and developers must use generative AI responsibly to ensure ethical practices.

    Learning Practice

  • 9.7

    Future Of Generative Ai

    The future of generative AI holds promise for complex collaborations between AI and humans but requires ethical advancements.

    Learning Practice

  • 9.2.1

    Two Main Techniques Used

    This section introduces two main techniques of generative AI: Generative Adversarial Networks (GANs) and Transformers.

    Learning Practice

  • 9.2.1.1

    Generative Adversarial Networks (Gans)

    Generative Adversarial Networks (GANs) involve a creative process between a generator and a discriminator to produce and validate realistic content.

    Learning Practice

  • 9.2.1.2

    Transformers (Like Gpt)

    Transformers are advanced neural networks that excel at natural language processing tasks like text generation and summarization.

    Learning Practice

  • 9.5.1

    Major Risks

    Generative AI has significant risks, including the potential for creating fake content, legal issues regarding plagiarism, and biases stemming from training data.

    Learning Practice

References

ch9.pdf

Class Notes

Memorization

What we have learnt

  • Generative AI creates new c...
  • Techniques like GANs and tr...
  • Generative AI presents both...

Final Test

Revision Tests