Nathan hosts Riley Goodside, the world's first staff prompt engineer at Scale AI, to discuss the evolution of prompt engineering. In this episode of The Cognitive Revolution, we explore how language models have progressed, making prompt engineering more like programming than poetry. Discover insights on enterprise AI applications, best practices for pushing LLMs to their limits, and the future of AI automation.
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CHAPTERS:
(00:00:00) About the Show
(00:00:23) Sponsor: WorkOS
(00:01:24) Introduction
(00:06:23) LLMs using LLMs
(00:09:38) Tool Use
(00:11:06) How to manage the breadth of the task
(00:14:51) Prompt engineering
(00:26:49) Multitasking fine-tuning
(00:31:49) Sponsors: Omneky | Squad
(00:33:36) Best models for fine-tuning
(00:36:41) The Platonic Representation Hypothesis
(00:42:02) How close are we to AGI?
(00:45:44) How do you know if youre being too ambitious?
(00:51:18) Best practices for generating good output
(00:54:33) Backfills and synthetic transformations
(00:56:59) Prompt engineering
(01:05:54) AGI, modalities, and the limits of training
(01:20:08) Solving the ARC Challenge
(01:23:20) How to Demonstrate Prompt Engineering Skills
(01:25:27) Outro
From Poetry to Programming: The Evolution of Prompt Engineering with Riley Goodside of Scale AI | "The Cognitive Revolution" | AI Builders, Researchers, and Live Player Analysis podcast - Listen or read transcript on Metacast
