Added Chapter 09

content/chapters/08_llm/08_03_emerging.md

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 title: "Chapter 08.03: Emergent Abilities"
 weight: 8003
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-Various researchers have reported that LLMs seem to have emergent abilities. These are sudden appearances of new abilities when Large Language Models (LLMs) are scaled up. In this section we introduce the concept of emergent abilities and discuss a potential counterargument for the concept of emergence.
+Various researchers have reported that LLMs seem to have emergent abilities. These are sudden appearances of new abilities when Large Language Models (LLMs) are scaled up. In this section we introduce the concept of emergent abilities and discuss a potential counter argument for the concept of emergence.
 
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content/chapters/09_rlhf/_index.md

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 title: "Chapter 9: Reinforcement Learning from Human Feedback (RLHF)"
 ---
 
-Here we cover the basics of RLHF and its related application.  
+In the context of natural language processing (NLP), RLHF (Reinforcement Learning from Human Feedback) involves training language models to generate text or perform tasks based on evaluative signals provided by human annotators or users. This technique allows NLP models to learn from human feedback, such as ratings or corrections, to improve their language understanding, generation, or task performance. By iteratively adjusting model parameters to maximize the reward signal derived from human feedback, RLHF enables models to adapt to specific preferences or requirements, leading to more accurate and contextually relevant outputs in various NLP applications.  
+
+### Lecture Slides
+
+{{< pdfjs file="https://github.com/slds-lmu/lecture_dl4nlp/blob/main/slides/chapter09-rlhf/slides-91-rlhf.pdf" >}}
+
+
+### Additional Resources
+
+- [Video Explaining RLHF](https://www.youtube.com/watch?v=qGyFrqc34yc)