39 Lessons on Building ML Systems, Scaling, Execution, and More
This title could be clearer and more informative.Try out Clickbait Shieldfor free (5 uses left this month).
A practitioner's distillation of 39 lessons from attending ML industry conferences in 2024, covering ML system design, scaling challenges, LLM economics and trust issues, evaluation frameworks, data flywheels, execution velocity, cross-functional collaboration, and conference culture. Key themes include starting simple before adding ML, investing early in reward functions and evals, designing systems to be model-agnostic, and balancing iteration speed with the patience required for genuine breakthroughs.
Table of contents
Building effective machine learning systemsProduction and scalingExecution and collaborationBuilding for usersSpeaking at and attending conferencesSimilar reading6 Impressions