Overview
Explore the transformative potential of large language models (LLMs) in this beginner-friendly conference talk. Delve into the history of LLMs, examine GPT-4's capabilities, and address important considerations such as CO2 emissions, hallucinations, and safety. Learn about the strengths and limitations of LLMs, discover general guidelines for selection and deployment, and master the art of prompting. Gain insights into effective techniques like the Feynman method, Pareto principle, and storytelling. Investigate the role of virtual assistants in automated spaces and explore real-world use cases. Equip yourself with the knowledge to harness the power of AI and adapt to the changing landscape of work, regardless of your background in technology.
Syllabus
Intro
History of large language models
GPT-4
CO2 emissions
Hallucinations & silent failures
What are LLMs good for?
What are LLMs not so good for?
Safety 101
General guidelines for selection & deployment
The fine art of prompting
The Feynman technique
The Pareto principle
Storytelling
Virtual assistants in automated space
Use cases
Outro
Taught by
GOTO Conferences