Generative_Artificiali_Presentation.pptx

Generative_Artificiali_Presentation.pptx

• 1.
  Unlocking the Powerof Generative AI From Concepts to Real-World Impact Your Name | Date | Organization
• 2.
  Agenda • • Whatis Generative AI? • • How it Works (Key Technologies) • • Use Cases Across Industries • • Risks & Ethical Considerations • • Future Outlook • • Q&A
• 3.
  What is GenerativeAI? • • AI that generates new content (text, images, audio, etc.) • • Examples: ChatGPT, DALL·E, Midjourney, GitHub Copilot • • Differentiator: Produces original content, not just classifications
• 4.
  Brief History • •2014: GANs introduced • • 2017: Transformers (Attention is All You Need) • • 2018–2020: GPT, BERT, T5 • • 2022+: Explosion in adoption (ChatGPT, Sora, Claude, Gemini)
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  How Does ItWork? • • Data Ingestion: Large-scale datasets • • Model Types: Transformers, GANs, Diffusion Models • • Training: Self-supervised, RLHF • • Output Generation: Sampling (top-k, top-p)
• 6.
  Use Cases: Text •• Customer support chatbots • • Content creation: blogs, emails • • Code generation: GitHub Copilot • • Translation, summarization
• 7.
  Use Cases: Images& Audio • • AI art generation • • Product design & fashion • • Voice synthesis, music creation • • Medical imaging support
• 8.
  Use Cases: Video& 3D • • Storyboarding, animation (e.g., Sora) • • Virtual environments (gaming, AR/VR) • • Architectural visualization
• 9.
  Industry Applications • Healthcare:Radiology, drug discovery • Finance: Report automation, fraud detection • Retail: Personalized ads, product design • Education: AI tutors, grading help • Legal: Contract review, summarization
• 10.
  Benefits • • Speedand scale • • Personalized experiences • • Creative ideation support • • Lower content production costs
• 11.
  Risks and Concerns •• Misinformation & hallucinations • • Bias & fairness • • Deepfakes & synthetic media • • IP and data privacy issues
• 12.
  Ethical Considerations • •Human-in-the-loop design • • Transparency & explainability • • Responsible AI frameworks • • Align AI with human values
• 13.
  The Future ofGenerative AI • • Multimodal AI (text, image, video) • • Efficient models on edge devices • • Open vs. closed-source AI • • Regulatory landscape evolving
• 14.
  Getting Started • •Tools: ChatGPT, Midjourney, Copilot, Runway • • Platforms: Hugging Face, OpenAI, Google Vertex AI • • Skills: Prompting, fine-tuning, ethics
• 15.
  Interactive Q&A • •Live questions or Slido • • Optional live prompt demo
• 16.
  Final Takeaways • •Generative AI is powerful and evolving • • Big opportunities across industries • • Use responsibly: stay curious, cautious, collaborative
• 17.
  Thank You • •Contact: Your Email / LinkedIn • • Feedback & Resources QR (optional)