Generative AI .pptx.....................

IOT

1. LINGARAJ APPA ENGINEERING COLLEGE BIDAR A Technical Seminar on Generative AI Under The Guidance of Prof : Veeresh Biradar Presented By : Vaishnavi Thakur USN : 3LA20CS040 Computer Science And Engineering

2. CONTENTS : WHAT IS GENERATIVE AI THE RISE OF GENERATIVE AI KEY GENERATIVE AI TECHNOLOGIES APPLICATIONS OF GENERATIVE AI OPPORTUNITIES AND CHALLENGES 6. ADVANTAGES OF GENERATIVE AI 7. ETHICAL CONSIDERATION 8. THE FUTURE OF GENERATIVE AI 9. CONCLUSION

3. Generative AI is a powerful technology that enables computers to create novel content, such as images, text, or audio, based on learning from large datasets. It has the potential to revolutionize how we interact with and create digital content. What is generative AI ?

4. The Rise of Generative AI In recent years, the field of Generative AI has experienced a rapid surge in advancements, driven by breakthroughs in machine learning techniques like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). These innovations have led to the development of highly sophisticated models capable of generating a wide range of content.

5. Keys of Generative AI Technologies

6. Key s of Generative AI Technologies Text Generation Language models like GPT-3 can generate human-like text, from creative writing to task- oriented dialogue. Image Generation Models like DALL-E and Stable Diffusion can create unique, high-quality images from textual descriptions. Audio/Music Generation Systems like Jukebox and MuseNet can compose original music and generate realistic- sounding audio.

7. Applications o f Generative AI 1 Content Creation Generating visual art, stock images, videos, and other media to support creative industries. 2 Personalization Customizing digital experiences, products, and services to individual user preferences . 3 Simulation Creating synthetic data for training AI models and testing complex systems . 4 Automation Streamlining workflows and reducing manual effort in various domains.

8. Opportunities and Challenges 1 Opportunities Unlocking new creative possibilities, enhancing productivity, and democratizing content creation . 2 Challenges Addressing bias, ensuring safety and security, and navigating ethical considerations .

9. Ethical Considerations Bias and Fairness Ensuring Generative AI models are trained on diverse and representative data to mitigate biases. Privacy and Security Protecting user privacy and preventing the misuse of generated content for malicious purposes. Transparency and Accountability Developing clear guidelines and regulations to ensure the responsible development and deployment of Generative AI. Social Impact Considering the broader societal implications of Generative AI and its potential to disrupt industries and change the nature of work .

10. The Future of Generative AI Advancements Continued improvements in model architecture, training techniques, and computing power will drive the capabilities of Generative AI. 1 2 Integration Generative AI will become more seamlessly integrated into various applications and workflows, transforming how we create and interact with digital content. 3 Responsible Development Ethical guidelines and regulatory frameworks will be crucial to ensure the safe and beneficial deployment of Generative AI.

11. Conclusion Potential Generative AI has immense potential to revolutionize how we c r e a t e , in t e r act with, and experience digital content. Collaboration By working together, researchers, developers, and policymakers can unlock the full potential of Generative AI while addressing its challenges. Responsible Path Navigating the responsible development and deployment of Generative AI will be crucial to ensuring its benefits are realized.

12. Thank You