Learn to Spell: Prompt Engineering (LLM Bootcamp)

New course announcement ✨ We're teaching an in-person LLM bootcamp in the SF Bay Area on November 14, 2023. Come join us if you want to see the most up-to-date materials building LLM-powered products and learn in a hands-on environment. https://www.scale.bythebay.io/llm-workshop Hope to see some of you there! --------------------------------------------------------------------------------------------- In this video, Charles gives high-level intuitions and a default playbook for prompting language models. We consider two very different sources of intuition: "language models are statistical models of text" and "prompts are magic spells". Then, we review prompting techniques, like decomposition, reasoning, and reflection. Download slides from the bootcamp website here: https://fullstackdeeplearning.com/llm-bootcamp/spring-2023/prompt-engineering/ Intro and outro music made with Riffusion: https://github.com/riffusion/riffusion Watch the rest of the LLM Bootcamp videos here: https://www.youtube.com/playlist?list=PL1T8fO7ArWleyIqOy37OVXsP4hFXymdOZ 00:00 Intro 02:15 Language models are statistical models of text 04:50 But "statistical model" gives bad intuition 08:35 Prompts are magic spells 09:57 Prompts are portals to alternate universes 16:42 A prompt can make a wish come true 23:03 A prompt can create a golem 27:10 Limitations of LLMs as simulators 32:17 Prompting techniques are mostly tricks 33:40 Few-shot learning isn't the right model for prompting 37:40 Character-level operations are hard 40:23 The prompting playbook: reasoning, reflection, & ensembling