In episode 75 of The Gradient Podcast, Daniel Bashir speaks to Riley Goodside.
Riley is a Staff Prompt Engineer at Scale AI. Riley began posting GPT-3 prompt examples and screenshot demonstrations in 2022. He previously worked as a data scientist at OkCupid, Grindr, and CopyAI.
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Outline:
(00:00) Intro
(01:37) Riley’s journey to becoming the first Staff Prompt Enginer
(02:00) data science background in online dating industry
(02:15) Sabbatical + catching up on LLM progress
(04:00) AI Dungeon and first taste of GPT-3
(05:10) Developing on codex, ideas about integrating codex with Jupyter Notebooks, start of posting on Twitter
(08:30) “LLM ethnography”
(09:12) The history of prompt engineering: in-context learning, Reinforcement Learning from Human Feedback (RLHF)
(10:20) Models used to be harder to talk to
(10:45) The three eras
(10:45) 1 - Pre-trained LM era—simple next-word predictors
(12:54) 2 - Instruction tuning
(16:13) 3 - RLHF and overcoming instruction tuning’s limitations
(19:24) Prompting as subtractive sculpting, prompting and AI safety
(21:17) Riley on RLHF and safety
(24:55) Riley’s most interesting experiments and observations
(25:50) Mode collapse in RLHF models
(29:24) Prompting models with very long instructions
(33:13) Explorations with regular expressions, chain-of-thought prompting styles
(36:32) Theories of in-context learning and prompting, why certain prompts work well
(42:20) Riley’s advice for writing better prompts
(49:02) Debates over prompt engineering as a career, relevance of prompt engineers
(58:55) Outro
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