Generative AI

Sudha Jamthe is a technology futurist, author of 7 books, educator, and independent researcher with 25+ years of entrepreneurial and operational experience in the technology industry. She is a LinkedIn Learning instructor for courses on AI, GenAI, and AI for the Internet of Things and autonomous vehicles. Her specialty is mentoring technology innovators, designers and business leaders using No-Code AI. She builds online learning communities at the Business school of AI with the WeeklyWed global speaker series. She is passionate about Gender Equality and hosts IoTWoman annually, showcasing 24 global women leaders in technology over 24 hours. She has produced courses about AI, AI ethics, and autonomous vehicles at Stanford Continuing Studies, Barcelona Technology School, Business School of AI, and EMBA Consortium at Lucas School of Business. She upskills researchers on language inclusion at Global South in AI and brings them to present at the NeurIPS conference. Her aspiration is a limitless world. In her spare time, Sudha enjoys chasing self-driving cars and hugging robots. She can be reached at sudhajamthe.com.

• 1. What is Generative AI, and Why Does it Matter? 2. Technology of Foundation Models, General Adversarial Networks (GAN), Synthetic Data, Attention, Diffusion Models 3. Generative AI Models, Models Explained in English, Research in GenAI, Model Modality, Semi-Supervised AI 4. Large Language Models, LLM, How LLM Works, State of research of LLMs, Ethical Implications of Building LLMs 5. LLM for Global Languages, Country-specific LLMs, Mistral, Aya 6. What is Hallucination, Causes, and the State of Research of Hallucination in LLMs 7. Data Fine-tuning and Retrieval Augmented Generation (RAG), Difference Between RAG and Fine-tuning, State of Research of Fine-tuning and RAG 8. LLM Capabilities, Reasoning Models, Q&A Models, State of Research in Reasoning 9. The API Economy, GenAI Market Trends, GenAI Applications 10. Industries impacted by GenAi: Software Engineering, Education, e-commerce, Customer Support 11. Ethical Product Design with GenAI, Prompt Engineering, and GenAI Middleware 12. Enterprise GenAI, Data Modeling, Automated Buildings 13. Ethical Responsible GenAI, which Industries are Impacted More by GenAI, Automation and Jobs, Gender Bias and Lack of Explainability 14. AI and Social Change, Anthropomorphism, Voice Clones and Deep Fakes, Competencies Needed for Success with GenAI 15. Appendix: Models for Reference, Research References, and Ethical Governance Frameworks