
Teaching Large Language Models to Reason with Reinforcement Learning with Alex Havrilla - #680
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Exploring Static and Dynamic Noise in Training Data for AI Models
This chapter explores the distinctions between static and dynamic noise in training data, highlighting their respective impacts on model outcomes. It reveals the surprising resilience of models to static noise, achieving high accuracy until noise levels reach critical thresholds.
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