Understanding Large Language Models Series

Learning Paradigms in LLMs: From Examples to Feedback

by Nat Currier 21 min read
AILarge Language ModelsMachine LearningTraining Methods
SERIES

Understanding Large Language Models

Part 18 of 26
Previous Real-Time vs. Latency in LLMs: Striking the Balance
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Excerpt

Explore the different approaches that define how large language models learn, from supervised learning to reinforcement learning from human feedback (RLHF), and understand how each method shapes AI behavior.

SERIES

Understanding Large Language Models

Part 18 of 26
Previous Real-Time vs. Latency in LLMs: Striking the Balance
Next Transformers Architecture Explained: The Engine Behind Modern LLMs