LLM Evals Lesson 2 Error Analysis
Notes from lesson 2 of Hamel and Shreya's LLM evaluation course - covering error analysis, open and axial coding, and systematic approaches to understanding where AI systems fail.
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Hamel & Shreya's LLM Evals Course: Lesson 1
Notes from the first lesson of Parlance Lab's Maven course on evaluating LLM applications - covering the Three Gulfs model and why eval is where most people get stuck.
Cogs / Interns / Human Tasks, a practical framework for AI transformation
Trying to blend together two AI Framework styling into one that's more practically useful
Synthesising a new framework for AI Transformation
I like bits of Brunig's and Mollick's AI frameworks, but neither quite works for me.
Error Analysis for Improving LLM Applications
A systematic approach to analysing and improving large language model applications through error analysis.
Why we need Experiment-based Roadmaps in the AI Product Era
Why evaluation-driven experimentation creates better roadmaps in AI products.