Introduction to Generative AI with Taksh

Introduction to Generative AI with Taksh

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  Introduction to Generative AI By23It067 Taksh Padmani
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  Outline  What isGenerative AI?  How Does Generative AI Work?  Types of Generative AI Models  Applications of Generative AI  Benefits of Generative AI  Challenges and Ethical Considerations  The Future of Generative AI  Summary
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  What is GenerativeAI?  AI that creates new content rather than just analyzing data  Can generate text, images, music, and more  Uses models trained on large datasets to learn patterns and produce original outputs
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  How Does GenerativeAI Work?  Trained on massive datasets using deep learning  Learns patterns, structures, and features of the input data  Generates new content by sampling from learned patterns  Examples: GPT (text), DALL·E (images), MusicLM (music)
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  Types of GenerativeAI Models  Generative Adversarial Networks (GANs): Two networks compete to improve output quality  Variational Autoencoders (VAEs): Encode data into a compressed form and reconstruct it  Transformers: Sequence-based models great for text and other sequential data
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  Applications of GenerativeAI  Content creation (articles, art, music)  Chatbots and virtual assistants  Code generation and software development  Data augmentation for training other AI models  Drug discovery and scientific research
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  Benefits of GenerativeAI  Speeds up creative processes  Enables personalization at scale  Assists in problem-solving and ideation  Opens new possibilities in entertainment and education
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  Challenges and EthicalConsiderations  Potential for misinformation and deepfakes  Copyright and intellectual property issues  Bias in training data leading to biased outputs  Need for transparency and responsible use
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  The Future ofGenerative AI  Increasingly realistic and useful AI-generated content  Integration into daily tools and workflows  Enhanced collaboration between humans and AI  Ongoing research to improve safety and ethics
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  Summary  Generative AIcreates new, original content  Uses advanced models like GANs and Transformers  Wide-ranging applications across industries  Important to consider ethical challenges