This webinar is meant to provide you an introduction to a typical workflow that you may encounter when creating a user/customer-facing application using LLMs. Due to the inherently probabilistic nature of their responses, LLMs are often not directly ready to be deployed to customer-facing applications - they require some deterministic guardrails and edge scenario handling in order for them to be used judiciously.
Agenda for the session
- Introduction to Prompt Engineering
- Moderation & Safety Checks for Input & Output Text Content
- Input Categorization, Information Retrieval and Response Generation
- Putting together a Customer-facing Workflow for an LLM Application
About Speakers
Dr. Davood Wadi
AI Research Scientist, intelChain
Davood Wadi is an AI Research Scientist at intelChain. Before joining intelChain, he excelled as an AI researcher and pursued his Ph.D. at HEC Montreal, renowned globally for its academic excellence. His interest in applying modern technologies to data sparked his tenure as a financial analyst, where he started incorporating mathematical methods into mass psychology to understand investment patterns. Davood’s expertise and interests include developing new algorithms for AI and ML applications, computer vision, NLP, Meta-Learning, and Consumer neuroscience.
