From Search to Answers, what you should know about RAG

From Search to Answers: What You Should Know About RAG
Join us for an evening exploring Retrieval-Augmented Generation (RAG), one of the most powerful techniques for building AI systems that deliver accurate, grounded responses.

What You'll Learn:

• The Evolution of Information Retrieval – how we got from traditional search to RAG
• RAG Framework Overview – understanding how it works under the hood
• Performance Optimization – what affects RAG speed, latency, and throughput
• Real-World Deployment – practical strategies for production systems
• Future Trends – where RAG is heading next

Speaker: Kelvin He, AI Data Scientist at Lenovo
Kelvin brings over ten years of experience transforming complex data into actionable business insights. His expertise spans the full spectrum of machine learning—from regression and classification to graph knowledge, causal ML, and the latest advances in large language models and RAG. He'll demystify these cutting-edge AI methods and share practical strategies you can apply immediately to your own projects.
Whether you're building AI applications, working with LLMs, or curious about how to make AI systems more reliable and contextual, this talk will give you the knowledge and tools to level up your RAG implementations.

Who Should Attend: AI practitioners, data scientists, ML engineers, software developers, and anyone interested in building better AI-powered applications.