Large Language Models (LLMs) and Generative AI

• To introduce participants to the architecture and capabilities of LLMs and Generative AI.
• To train participants in building, fine-tuning, and deploying LLM-based solutions.
• To explore diverse applications of generative AI across industries.
• To discuss ethical challenges and best practices in the use of LLMs and generative technologies.
• To prepare participants for roles in AI innovation and creative technology development.

Day 1: Introduction and Fundamentals

Session Title: Foundations of Large Language Models and Generative AI

1. Overview of LLMs and Generative AI
   • What are Large Language Models?
   • Evolution of Generative AI (from GPT to GPT-X).
   • Key applications in research, academia, and industry.
2. Core Concepts
   • Natural Language Processing (NLP) basics.
   • The architecture of LLMs: Transformer models and attention mechanisms.
   • Ethical considerations: Bias, fairness, and responsible AI.
3. Interactive Hands-on Activity
   • Exploring pre-trained LLMs using open-source platforms like Hugging Face.
   • Text generation and summarization examples.

Day 2: Hands-On with Generative AI

Session Title: Practical Applications of Generative AI

1. Applications Across Domains
   • Content creation: Automated writing and summarization.
   • Research and teaching: Literature reviews and quiz generation.
   • Industry use cases: Customer service, chatbots, and data analysis.
2. Advanced Features and Fine-Tuning
   • Customizing pre-trained models for specific domains.
   • Techniques for fine-tuning LLMs.
3. Interactive Hands-on Activity
   • Experimenting with fine-tuning models for domain-specific tasks (e.g., research paper abstract generation, educational content creation).
   • Participants will use platforms like Google Colab for practical implementation.

Day 3: Future Trends and Innovation

Session Title: Scaling LLMs and Driving Innovations

1. Emerging Trends in Generative AI
   • Scaling models: Challenges and opportunities.
   • Multimodal AI: Combining text, image, and video generation.
   • Integrating LLMs with other technologies (e.g., IoT, blockchain).
2. Collaborative AI and Innovations
   • Co-creative systems: AI-human collaboration.
   • Open research and AI democratization.
3. Interactive Hands-on Activity
   • Building a simple chatbot or assistant using pre-trained LLMs.
   • Discussing deployment considerations in research, education, and industry.
4. Closing Remarks and Q&A
   • Recap of the workshop.
   • Open discussion on implementing learnings in participants’ fields.

• Mastery of the principles and techniques behind LLMs and Generative AI
• Proficiency in fine-tuning and deploying LLMs for practical applications
• Skills to create AI-driven content and conversational systems
• Awareness of ethical, societal, and technical challenges in generative AI
• Insights into the latest trends and innovations in LLMs

• AI and ML enthusiasts
• Data scientists and software engineers
• Content creators and marketers exploring generative AI
• Academics, students, and researchers in AI and natural language processing
• Professionals interested in leveraging LLMs for industry-specific applications