Modern AI Landspace & Foundation Models
Kick off with a brief history of Artificial Intelligence. From Turing Test in 1950s to Transformers in 2010s.
You’ll delve into the emergence of Foundation Models, focusing on the revolutionary Transformer architecture. Developed by researchers from Google and the University of Toronto in 2017, Transformers have fundamentally reshaped AI capabilities with their innovative approach, replacing sequential processing with parallel execution. Key innovations you'll explore include positional encodings, attention mechanisms, and self-attention—each empowering models to grasp context and vastly accelerate training processes.
Deepen your practical understanding of how Foundation Models are trained, exploring the critical convergence of big data, advanced algorithms, and computing power. Learn best practices for interacting with these models, mastering tokens, context length, temperature, and effectively managing model configurations and hallucinations.
Lastly, understand the vital importance of responsible AI development. Explore the ethical considerations of model bias, transparency, regulatory compliance, data privacy, and accountability, ensuring your AI solutions remain trustworthy and impactful.
Step confidently into the future of AI—starting here, in Module 1.
- 1Introduction to the Course
- 2A Brief History of AI - From Turing To Transformers
- 3How Foundation Models like GPT-4 are trained
- 4Post Training a Foundation Model
- 5Interacting with a LLM using a vendor console