This advanced-level course is designed for researchers, practitioners, and graduate students interested in the cutting-edge developments in artificial intelligence. The course delves deep into the latest research trends, focusing on three primary areas: Large Language Models (LLMs), Large Visual Models (LVMs), and Applied AI in industry tasks. Through a combination of lectures, case studies, and hands-on projects, participants will gain a comprehensive understanding of the theoretical underpinnings and practical applications of these technologies.
To provide an in-depth understanding of the architecture, capabilities, and limitations of Large Language Models (LLMs).
To explore the advancements in Large Visual Models (LVMs), including their applications in image and video processing.
To examine how AI is being applied in various industry sectors, focusing on real-world challenges and solutions.
To equip participants with the skills to critically evaluate and contribute to the latest AI research.
Architecture - Data - Optimization - Systems
Overview of LLMs: History and Evolution
Key Concepts: Transformer Models, Attention Mechanisms, and Pre-training Techniques
Case Studies: GPT-3, BERT, and T5
Ethical Considerations and Bias in LLMs
Introduction to LVMs: From Convolutional Neural Networks to Vision Transformers
Advanced Techniques: Object Detection, Image Segmentation, and Generative Models
Case Studies: DALL-E, CLIP, and VisualGPT
Research Focus 3: Applied AI in Industry Tasks. Applications in Healthcare, Autonomous Vehicles, and Media, Pharma, etc
Emerging Trends in AI: Multimodal Learning and Explainable AI
Collaborative Research Opportunities: Industry-Academia Partnerships
Preparing for the Future: Skills and Knowledge Required for AI Researchers